Data-Driven Execution of Multi-Layered Networks for Automatic Speech Recognition. - Renato de Mori; Yoshua Bengio; Régis Cardin (AAAI, 1988)

Use of neural networks for the recognition of place of articulation. - Yoshua Bengio; Renato De Mori (ICASSP, 1988)

Use of Multi-Layered Networks for Coding Speech with Phonetic Features. - Yoshua Bengio; Régis Cardin; Renato de Mori; Piero Cosi (NIPS, 1988)

Speech coding with multi-layer networks. - Yoshua Bengio; Régis Cardin; Piero Cosi; Renato De Mori (ICASSP, 1989)

On the Generalization Capability of Multi-Layered Networks in the Extraction of Speech Properties. - Renato de Mori; Yoshua Bengio; Piero Cosi (IJCAI, 1989)

Speech coding with multilayer networks. - Yoshua Bengio; Régis Cardin; Piero Cosi; Renato De Mori; Ettore Merlo (NATO Neurocomputing, 1989)

A Neural Network to Detect Homologies in Proteins. - Yoshua Bengio; Samy Bengio; Yannick Pouliot; Patrick Agin (NIPS, 1989)

Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge. - Yoshua Bengio; Renato de Mori; Régis Cardin (NIPS, 1989)

Programmable Execution of Multi-Layered Networks for Automatic Speech Recognition. - Yoshua Bengio; Régis Cardin; Renato de Mori; Ettore Merlo (Commun. ACM, 1989)

A hybrid coder for hidden Markov models using a recurrent neural network. - Yoshua Bengio; Régis Cardin; Renato De Mori; Yves Normandin (ICASSP, 1990)

Efficient recognition of immunoglobulin domains from amino acid sequences using a neural network. - Yoshua Bengio; Yannick Pouliot (Comput. Appl. Biosci., 1990)

Phonetically-based multi-layered neural networks for vowel classification. - Piero Cosi; Yoshua Bengio; Renato de Mori (Speech Commun., 1990)

A comparative study on hybrid acoustic phonetic decoders based on artificial neural networks. - Yoshua Bengio; Renato de Mori; Giovanni Flammia; Ralf Kompe (EUROSPEECH, 1991)

Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation. - Yoshua Bengio; Renato de Mori; Giovanni Flammia; Ralf Kompe (NIPS, 1991)

Learning the dynamic nature of speech with back-propagation for sequences. - Yoshua Bengio; Renato de Mori; Marco Gori (Pattern Recognit. Lett., 1992)

Phonetically motivated acoustic parameters for continuous speech recognition using artificial neural networks. - Yoshua Bengio; Renato de Mori; Giovanni Flammia; Ralf Kompe (Speech Commun., 1992)

Global optimization of a neural network-hidden Markov model hybrid. - Yoshua Bengio; Renato De Mori; Giovanni Flammia; Ralf Kompe (IEEE Trans. Neural Networks, 1992)

The problem of learning long-term dependencies in recurrent networks. - Yoshua Bengio; Paolo Frasconi; Patrice Y. Simard (ICNN, 1993)

Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models. - Yoshua Bengio; Yann LeCun; Donnie Henderson (NIPS, 1993)

Credit Assignment through Time: Alternatives to Backpropagation. - Yoshua Bengio; Paolo Frasconi (NIPS, 1993)

A Connectionist Approach to Speech Recognition. - Yoshua Bengio (Int. J. Pattern Recognit. Artif. Intell., 1993)

Use of Genetic Programming for the Search of a New Learning Rule for Neural Networks. - Samy Bengio; Yoshua Bengio; Jocelyn Cloutier (International Conference on Evolutionary Computation, 1994)

Word normalization for online handwritten word recognition. - Yoshua Bengio; Yann LeCun (ICPR (2), 1994)

An EM approach to grammatical inference: input/output HMMs. - Paolo Frasconi; Yoshua Bengio (ICPR (2), 1994)

Word-level training of a handwritten word recognizer based on convolutional neural networks. - Yann LeCun; Yoshua Bengio (ICPR (2), 1994)

An Input Output HMM Architecture. - Yoshua Bengio; Paolo Frasconi (NIPS, 1994)

Diffusion of Credit in Markovian Models. - Yoshua Bengio; Paolo Frasconi (NIPS, 1994)

Convergence Properties of the K-Means Algorithms. - Léon Bottou; Yoshua Bengio (NIPS, 1994)

Learning long-term dependencies with gradient descent is difficult. - Yoshua Bengio; Patrice Y. Simard; Paolo Frasconi (IEEE Trans. Neural Networks, 1994)

Recurrent Neural Networks for Missing or Asynchronous Data. - Yoshua Bengio; Francois Gingras (NIPS, 1995)

Hierarchical Recurrent Neural Networks for Long-Term Dependencies. - Salah El Hihi; Yoshua Bengio (NIPS, 1995)

Diffusion of Context and Credit Information in Markovian Models. - Yoshua Bengio; Paolo Frasconi (J. Artif. Intell. Res., 1995)

LeRec: a NN/HMM hybrid for on-line handwriting recognition. - Yoshua Bengio; Yann LeCun; Craig R. Nohl; Christopher J. C. Burges (Neural Comput., 1995)

On the search for new learning rules for ANNs. - Samy Bengio; Yoshua Bengio; Jocelyn Cloutier (Neural Process. Lett., 1995)

Multi-Task Learning for Stock Selection. - Joumana Ghosn; Yoshua Bengio (NIPS, 1996)

Input-output HMMs for sequence processing. - Yoshua Bengio; Paolo Frasconi (IEEE Trans. Neural Networks, 1996)

Global Training of Document Processing Systems Using Graph Transformer Networks. - Léon Bottou; Yoshua Bengio; Yann LeCun (CVPR, 1997)

AdaBoosting Neural Networks: Application to on-line Character Recognition. - Holger Schwenk; Yoshua Bengio (ICANN, 1997)

Reading checks with multilayer graph transformer networks. - Yann LeCun; Léon Bottou; Yoshua Bengio (ICASSP, 1997)

Discriminative feature and model design for automatic speech recognition. - Mazin Rahim; Yoshua Bengio; Yann LeCun (EUROSPEECH, 1997)

Shared Context Probabilistic Transducers. - Yoshua Bengio; Samy Bengio; Jean-Franc Isabelle; Yoram Singer (NIPS, 1997)

Training Methods for Adaptive Boosting of Neural Networks. - Holger Schwenk; Yoshua Bengio (NIPS, 1997)

Using a Financial Training Criterion Rather than a Prediction Criterion. - Yoshua Bengio (Int. J. Neural Syst., 1997)

Browsing through High Quality Document Images with DjVu. - Patrick Haffner; Léon Bottou; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (ADL, 1998)

The Z-Coder Adaptive Binary Coder. - Léon Bottou; Paul G. Howard; Yoshua Bengio (Data Compression Conference, 1998)

A Memory-Efficient Adaptive Huffman Coding Algorthm for Very Large Sets of Symbols. - Steven Pigeon; Yoshua Bengio (Data Compression Conference, 1998)

Support vector machines for improving the classification of brain PET images. - Martin Bonneville; Jean Meunier; Yoshua Bengio; Jean-Paul Soucy (Image Processing, 1998)

Gaussian Mixture Densities for Classification of Nuclear Power Plant Data. - Yoshua Bengio; Francois Gingras; Bernard Goulard; Jean-Marc Lina; Keith Scott (Comput. Artif. Intell., 1998)

High quality document image compression with "DjVu". - Léon Bottou; Patrick Haffner; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (J. Electronic Imaging, 1998)

Gradient-based learning applied to document recognition. - Yann LeCun; Léon Bottou; Yoshua Bengio; Patrick Haffner (Proc. IEEE, 1998)

Binary Pseudowavelets and Applications to Bilevel Image Processing. - Steven Pigeon; Yoshua Bengio (Data Compression Conference, 1999)

Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks. - Yoshua Bengio; Samy Bengio (NIPS, 1999)

Object Recognition with Gradient-Based Learning. - Yann LeCun; Patrick Haffner; Léon Bottou; Yoshua Bengio (Shape, Contour and Grouping in Computer Vision, 1999)

Stochastic Learning of Strategic Equilibria for Auctions. - Samy Bengio; Yoshua Bengio; Jacques Robert; Gilles Bélanger (Neural Comput., 1999)

Continuous Optimization of Hyper-Parameters. - Yoshua Bengio (IJCNN (1), 2000)

Probabilistic Neural Network Models for Sequential Data. - Yoshua Bengio (IJCNN (5), 2000)

A Neural Support Vector Network Architecture with Adaptive Kernels. - Pascal Vincent; Yoshua Bengio (IJCNN (5), 2000)

A Neural Probabilistic Language Model. - Yoshua Bengio; Réjean Ducharme; Pascal Vincent (NIPS, 2000)

Incorporating Second-Order Functional Knowledge for Better Option Pricing. - Charles Dugas; Yoshua Bengio; François Bélisle; Claude Nadeau; René Garcia (NIPS, 2000)

Gradient-Based Optimization of Hyperparameters. - Yoshua Bengio (Neural Comput., 2000)

Boosting Neural Networks. - Holger Schwenk; Yoshua Bengio (Neural Comput., 2000)

Taking on the curse of dimensionality in joint distributions using neural networks. - Samy Bengio; Yoshua Bengio (IEEE Trans. Neural Networks Learn. Syst., 2000)

Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference. - Nicolas Chapados; Yoshua Bengio; Pascal Vincent; Joumana Ghosn; Charles Dugas; Ichiro Takeuchi; Linyan Meng (NIPS, 2001)

K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms. - Pascal Vincent; Yoshua Bengio (NIPS, 2001)

Topic Segmentation : A First Stage to Dialog-Based Information Extraction. - Narjès Boufaden; Guy Lapalme; Yoshua Bengio (NLPRS, 2001)

Experiments on the application of IOHMMs to model financial returns series. - Yoshua Bengio; Vincent-Philippe Lauzon; Réjean Ducharme (IEEE Trans. Neural Networks, 2001)

Cost functions and model combination for VaR-based asset allocation using neural networks. - Nicolas Chapados; Yoshua Bengio (IEEE Trans. Neural Networks, 2001)

Manifold Parzen Windows. - Pascal Vincent; Yoshua Bengio (NIPS, 2002)

Metric-based model selection for time-series forecasting. - Yoshua Bengio; Nicolas Chapados (NNSP, 2002)

Segmentation en thèmes de conversations téléphoniques : traitement en amont pour l'extraction d'information. - Narjès Boufaden; Guy Lapalme; Yoshua Bengio (TALN (Posters), 2002)

Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination. - Yoshua Bengio; Dale Schuurmans (Mach. Learn., 2002)

Model Selection for Small Sample Regression. - Olivier Chapelle; Vladimir Vapnik; Yoshua Bengio (Mach. Learn., 2002)

Kernel Matching Pursuit. - Pascal Vincent; Yoshua Bengio (Mach. Learn., 2002)

A Parallel Mixture of SVMs for Very Large Scale Problems. - Ronan Collobert; Samy Bengio; Yoshua Bengio (Neural Comput., 2002)

Robust Regression with Asymmetric Heavy-Tail Noise Distributions. - Ichiro Takeuchi; Yoshua Bengio; Takafumi Kanamori (Neural Comput., 2002)

Quick Training of Probabilistic Neural Nets by Importance Sampling. - Yoshua Bengio; Jean-Sébastien Senecal (AISTATS, 2003)

Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering. - Yoshua Bengio; Jean-François Paiement; Pascal Vincent; Olivier Delalleau; Nicolas Le Roux; Marie Ouimet (NIPS, 2003)

Scaling Large Learning Problems with Hard Parallel Mixtures. - Ronan Collobert; Yoshua Bengio; Samy Bengio (Int. J. Pattern Recognit. Artif. Intell., 2003)

Extensions to Metric-Based Model Selection. - Yoshua Bengio; Nicolas Chapados (J. Mach. Learn. Res., 2003)

A Neural Probabilistic Language Model. - Yoshua Bengio; Réjean Ducharme; Pascal Vincent; Christian Janvin (J. Mach. Learn. Res., 2003)

Inference for the Generalization Error. - Claude Nadeau; Yoshua Bengio (Mach. Learn., 2003)

Bias learning, knowledge sharing. - Joumana Ghosn; Yoshua Bengio (IEEE Trans. Neural Networks, 2003)

Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models. - Indrajit Bhattacharya; Lise Getoor; Yoshua Bengio (ACL, 2004)

Non-Local Manifold Tangent Learning. - Yoshua Bengio; Martin Monperrus (NIPS, 2004)

Semi-supervised Learning by Entropy Minimization. - Yves Grandvalet; Yoshua Bengio (NIPS, 2004)

Brain Inspired Reinforcement Learning. - François Rivest; Yoshua Bengio; John Kalaska (NIPS, 2004)

Approche statistique pour le repérage de mots informatifs dans les textes oraux. - Narjès Boufaden; Yoshua Bengio; Guy Lapalme (TALN (Articles longs), 2004)

Locally Linear Embedding for dimensionality reduction in QSAR. - Pierre-Jean L'Heureux; Julie Carreau; Yoshua Bengio; Olivier Delalleau; Shi Yi Yue (J. Comput. Aided Mol. Des., 2004)

No Unbiased Estimator of the Variance of K-Fold Cross-Validation. - Yoshua Bengio; Yves Grandvalet (J. Mach. Learn. Res., 2004)

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA. - Yoshua Bengio; Olivier Delalleau; Nicolas Le Roux; Jean-François Paiement; Pascal Vincent; Marie Ouimet (Neural Comput., 2004)

Efficient Non-Parametric Function Induction in Semi-Supervised Learning. - Olivier Delalleau; Yoshua Bengio; Nicolas Le Roux (AISTATS, 2005)

Hierarchical Probabilistic Neural Network Language Model. - Frederic Morin; Yoshua Bengio (AISTATS, 2005)

Greedy Spectral Embedding. - Marie Ouimet; Yoshua Bengio (AISTATS, 2005)

The Curse of Highly Variable Functions for Local Kernel Machines. - Yoshua Bengio; Olivier Delalleau; Nicolas Le Roux (NIPS, 2005)

Non-Local Manifold Parzen Windows. - Yoshua Bengio; Hugo Larochelle; Pascal Vincent (NIPS, 2005)

Convex Neural Networks. - Yoshua Bengio; Nicolas Le Roux; Pascal Vincent; Olivier Delalleau; Patrice Marcotte (NIPS, 2005)

Label Propagation and Quadratic Criterion. - Yoshua Bengio; Olivier Delalleau; Nicolas Le Roux (Semi-Supervised Learning, 2006)

Large-Scale Algorithms. - Olivier Delalleau; Yoshua Bengio; Nicolas Le Roux (Semi-Supervised Learning, 2006)

Entropy Regularization. - Yves Grandvalet; Yoshua Bengio (Semi-Supervised Learning, 2006)

Spectral Dimensionality Reduction. - Yoshua Bengio; Olivier Delalleau; Nicolas Le Roux; Jean-François Paiement; Pascal Vincent; Marie Ouimet (Feature Extraction, 2006)

The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization. - Nicolas Chapados; Yoshua Bengio (Canadian AI, 2006)

Greedy Layer-Wise Training of Deep Networks. - Yoshua Bengio; Pascal Lamblin; Dan Popovici; Hugo Larochelle (NIPS, 2006)

Collaborative Filtering on a Family of Biological Targets. - Dumitru Erhan; Pierre-Jean L'Heureux; Shi Yi Yue; Yoshua Bengio (J. Chem. Inf. Model., 2006)

Nonlocal Estimation of Manifold Structure. - Yoshua Bengio; Martin Monperrus; Hugo Larochelle (Neural Comput., 2006)

An empirical evaluation of deep architectures on problems with many factors of variation. - Hugo Larochelle; Dumitru Erhan; Aaron C. Courville; James Bergstra; Yoshua Bengio (ICML, 2007)

Augmented Functional Time Series Representation and Forecasting with Gaussian Processes. - Nicolas Chapados; Yoshua Bengio (NIPS, 2007)

Learning the 2-D Topology of Images. - Nicolas Le Roux; Yoshua Bengio; Pascal Lamblin; Marc Joliveau; Balázs Kégl (NIPS, 2007)

Topmoumoute Online Natural Gradient Algorithm. - Nicolas Le Roux; Pierre-Antoine Manzagol; Yoshua Bengio (NIPS, 2007)

Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization. - Nicolas Chapados; Yoshua Bengio (J. Comput., 2007)

A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data. - Julie Carreau; Yoshua Bengio (AISTATS, 2007)

Continuous Neural Networks. - Nicolas Le Roux; Yoshua Bengio (AISTATS, 2007)

Zero-data Learning of New Tasks. - Hugo Larochelle; Dumitru Erhan; Yoshua Bengio (AAAI, 2008)

Classification using discriminative restricted Boltzmann machines. - Hugo Larochelle; Yoshua Bengio (ICML, 2008)

Extracting and composing robust features with denoising autoencoders. - Pascal Vincent; Hugo Larochelle; Yoshua Bengio; Pierre-Antoine Manzagol (ICML, 2008)

Representational Power of Restricted Boltzmann Machines and Deep Belief Networks. - Nicolas Le Roux; Yoshua Bengio (Neural Comput., 2008)

Neural net language models. - Yoshua Bengio (Scholarpedia, 2008)

Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model. - Yoshua Bengio; Jean-Sébastien Senecal (IEEE Trans. Neural Networks, 2008)

Curriculum learning. - Yoshua Bengio; Jérôme Louradour; Ronan Collobert; Jason Weston (ICML, 2009)

Workshop summary: Workshop on learning feature hierarchies. - Kai Yu; Ruslan Salakhutdinov; Yann LeCun; Geoffrey E. Hinton; Yoshua Bengio (ICML, 2009)

Quadratic Features and Deep Architectures for Chunking. - Joseph P. Turian; James Bergstra; Yoshua Bengio (HLT-NAACL (Short Papers), 2009)

Slow, Decorrelated Features for Pretraining Complex Cell-like Networks. - James Bergstra; Yoshua Bengio (NIPS, 2009)

An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism. - Aaron C. Courville; Douglas Eck; Yoshua Bengio (NIPS, 2009)

Learning Deep Architectures for AI. - Yoshua Bengio (Found. Trends Mach. Learn., 2009)

Incorporating Functional Knowledge in Neural Networks. - Charles Dugas; Yoshua Bengio; François Bélisle; Claude Nadeau; René Garcia (J. Mach. Learn. Res., 2009)

The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training. - Dumitru Erhan; Pierre-Antoine Manzagol; Yoshua Bengio; Samy Bengio; Pascal Vincent (AISTATS, 2009)

Exploring Strategies for Training Deep Neural Networks. - Hugo Larochelle; Yoshua Bengio; Jérôme Louradour; Pascal Lamblin (J. Mach. Learn. Res., 2009)

Justifying and Generalizing Contrastive Divergence. - Yoshua Bengio; Olivier Delalleau (Neural Comput., 2009)

A Hybrid Pareto Mixture for Conditional Asymmetric Fat-Tailed Distributions. - Julie Carreau; Yoshua Bengio (IEEE Trans. Neural Networks, 2009)

Word Representations: A Simple and General Method for Semi-Supervised Learning. - Joseph P. Turian; Lev-Arie Ratinov; Yoshua Bengio (ACL, 2010)

Learning Tags that Vary Within a Song. - Michael I. Mandel; Douglas Eck; Yoshua Bengio (ISMIR, 2010)

Theano: A CPU and GPU Math Compiler in Python. - James Bergstra; Olivier Breuleux; Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; Guillaume Desjardins; Joseph P. Turian; David Warde-Farley; Yoshua Bengio (SciPy, 2010)

Decision trees do not generalize to new variations. - Yoshua Bengio; Olivier Delalleau; Clarence Simard (Comput. Intell., 2010)

Deep Self-Taught Learning for Handwritten Character Recognition - Frédéric Bastien; Yoshua Bengio; Arnaud Bergeron; Nicolas Boulanger-Lewandowski; Thomas M. Breuel; Youssouf Chherawala; Moustapha Cissé; Myriam Côté; Dumitru Erhan; Jeremy Eustache; Xavier Glorot; Xavier Muller; et al. (CoRR, 2010)

Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs - Guillaume Desjardins; Aaron C. Courville; Yoshua Bengio (CoRR, 2010)

Alternative time representation in dopamine models. - François Rivest; John Kalaska; Yoshua Bengio (J. Comput. Neurosci., 2010)

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines. - Guillaume Desjardins; Aaron C. Courville; Yoshua Bengio; Pascal Vincent; Olivier Delalleau (AISTATS, 2010)

Why Does Unsupervised Pre-training Help Deep Learning? - Dumitru Erhan; Yoshua Bengio; Aaron C. Courville; Pierre-Antoine Manzagol; Pascal Vincent; Samy Bengio (J. Mach. Learn. Res., 2010)

Why Does Unsupervised Pre-training Help Deep Learning? - Dumitru Erhan; Aaron C. Courville; Yoshua Bengio; Pascal Vincent (AISTATS, 2010)

Understanding the difficulty of training deep feedforward neural networks. - Xavier Glorot; Yoshua Bengio (AISTATS, 2010)

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. - Pascal Vincent; Hugo Larochelle; Isabelle Lajoie; Yoshua Bengio; Pierre-Antoine Manzagol (J. Mach. Learn. Res., 2010)

Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest. - Hugo Larochelle; Yoshua Bengio; Joseph P. Turian (Neural Comput., 2010)

Deep Belief Networks Are Compact Universal Approximators. - Nicolas Le Roux; Yoshua Bengio (Neural Comput., 2010)

Learning Structured Embeddings of Knowledge Bases. - Antoine Bordes; Jason Weston; Ronan Collobert; Yoshua Bengio (AAAI, 2011)

On the Expressive Power of Deep Architectures. - Yoshua Bengio; Olivier Delalleau (ALT, 2011)

Unsupervised Models of Images by Spikeand-Slab RBMs. - Aaron C. Courville; James Bergstra; Yoshua Bengio (ICML, 2011)

Large-Scale Learning of Embeddings with Reconstruction Sampling. - Yann N. Dauphin; Xavier Glorot; Yoshua Bengio (ICML, 2011)

Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach. - Xavier Glorot; Antoine Bordes; Yoshua Bengio (ICML, 2011)

Contractive Auto-Encoders: Explicit Invariance During Feature Extraction. - Salah Rifai; Pascal Vincent; Xavier Muller; Xavier Glorot; Yoshua Bengio (ICML, 2011)

Temporal Pooling and Multiscale Learning for Automatic Annotation and Ranking of Music Audio. - Philippe Hamel; Simon Lemieux; Yoshua Bengio; Douglas Eck (ISMIR, 2011)

On learning distributed representations of semantics. - Yoshua Bengio (MLSLP, 2011)

Algorithms for Hyper-Parameter Optimization. - James Bergstra; Rémi Bardenet; Yoshua Bengio; Balázs Kégl (NIPS, 2011)

Shallow vs. Deep Sum-Product Networks. - Olivier Delalleau; Yoshua Bengio (NIPS, 2011)

On Tracking The Partition Function. - Guillaume Desjardins; Aaron C. Courville; Yoshua Bengio (NIPS, 2011)

The Manifold Tangent Classifier. - Salah Rifai; Yann N. Dauphin; Pascal Vincent; Yoshua Bengio; Xavier Muller (NIPS, 2011)

Higher Order Contractive Auto-Encoder. - Salah Rifai; Grégoire Mesnil; Pascal Vincent; Xavier Muller; Yoshua Bengio; Yann N. Dauphin; Xavier Glorot (ECML/PKDD (2), 2011)

Autotagging music with conditional restricted Boltzmann machines - Michael I. Mandel; Razvan Pascanu; Hugo Larochelle; Yoshua Bengio (CoRR, 2011)

Adding noise to the input of a model trained with a regularized objective - Salah Rifai; Xavier Glorot; Yoshua Bengio; Pascal Vincent (CoRR, 2011)

Learning invariant features through local space contraction - Salah Rifai; Xavier Muller; Xavier Glorot; Grégoire Mesnil; Yoshua Bengio; Pascal Vincent (CoRR, 2011)

Towards Open-Text Semantic Parsing via Multi-Task Learning of Structured Embeddings - Antoine Bordes; Xavier Glorot; Jason Weston; Yoshua Bengio (CoRR, 2011)

The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All) - James Bergstra; Aaron C. Courville; Yoshua Bengio (CoRR, 2011)

Discussion of "The Neural Autoregressive Distribution Estimator". - Yoshua Bengio (AISTATS, 2011)

Deep Learners Benefit More from Out-of-Distribution Examples. - Yoshua Bengio; Frédéric Bastien; Arnaud Bergeron; Nicolas Boulanger-Lewandowski; Thomas M. Breuel; Youssouf Chherawala; Moustapha Cissé; Myriam Côté; Dumitru Erhan; Jeremy Eustache; Xavier Glorot; Xavier Muller; et al. (AISTATS, 2011)

A Spike and Slab Restricted Boltzmann Machine. - Aaron C. Courville; James Bergstra; Yoshua Bengio (AISTATS, 2011)

Deep Sparse Rectifier Neural Networks. - Xavier Glorot; Antoine Bordes; Yoshua Bengio (AISTATS, 2011)

Suitability of V1 Energy Models for Object Classification. - James Bergstra; Yoshua Bengio; Jérôme Louradour (Neural Comput., 2011)

Quickly Generating Representative Samples from an RBM-Derived Process. - Olivier Breuleux; Yoshua Bengio; Pascal Vincent (Neural Comput., 2011)

Contextual tag inference. - Michael I. Mandel; Razvan Pascanu; Douglas Eck; Yoshua Bengio; Luca Maria Aiello; Rossano Schifanella; Filippo Menczer (ACM Trans. Multim. Comput. Commun. Appl., 2011)

Deep Learning for NLP (without Magic). - Richard Socher; Yoshua Bengio; Christopher D. Manning (ACL (Tutorial Abstracts), 2012)

Disentangling Factors of Variation for Facial Expression Recognition. - Salah Rifai; Yoshua Bengio; Aaron C. Courville; Pascal Vincent; Mehdi Mirza (ECCV (6), 2012)

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription. - Nicolas Boulanger-Lewandowski; Yoshua Bengio; Pascal Vincent (ICML, 2012)

Large-Scale Feature Learning With Spike-and-Slab Sparse Coding. - Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (ICML, 2012)

A Generative Process for Contractive Auto-Encoders. - Salah Rifai; Yann N. Dauphin; Pascal Vincent; Yoshua Bengio (ICML, 2012)

Discriminative Non-negative Matrix Factorization for Multiple Pitch Estimation. - Nicolas Boulanger-Lewandowski; Yoshua Bengio; Pascal Vincent (ISMIR, 2012)

Building Musically-relevant Audio Features through Multiple Timescale Representations. - Philippe Hamel; Yoshua Bengio; Douglas Eck (ISMIR, 2012)

Detonation Classification from acoustic Signature with the Restricted Boltzmann Machine. - Yoshua Bengio; Nicolas Chapados; Olivier Delalleau; Hugo Larochelle; Xavier Saint-Mleux; Christian Hudon; Jérôme Louradour (Comput. Intell., 2012)

Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery - Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (CoRR, 2012)

Evolving Culture vs Local Minima - Yoshua Bengio (CoRR, 2012)

On Training Deep Boltzmann Machines - Guillaume Desjardins; Aaron C. Courville; Yoshua Bengio (CoRR, 2012)

Practical recommendations for gradient-based training of deep architectures - Yoshua Bengio (CoRR, 2012)

Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives - Yoshua Bengio; Aaron C. Courville; Pascal Vincent (CoRR, 2012)

Implicit Density Estimation by Local Moment Matching to Sample from Auto-Encoders - Yoshua Bengio; Guillaume Alain; Salah Rifai (CoRR, 2012)

Efficient EM Training of Gaussian Mixtures with Missing Data - Olivier Delalleau; Aaron C. Courville; Yoshua Bengio (CoRR, 2012)

Disentangling Factors of Variation via Generative Entangling - Guillaume Desjardins; Aaron C. Courville; Yoshua Bengio (CoRR, 2012)

Understanding the exploding gradient problem - Razvan Pascanu; Tomás Mikolov; Yoshua Bengio (CoRR, 2012)

Theano: new features and speed improvements - Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; James Bergstra; Ian J. Goodfellow; Arnaud Bergeron; Nicolas Bouchard; David Warde-Farley; Yoshua Bengio (CoRR, 2012)

Joint Training of Deep Boltzmann Machines - Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (CoRR, 2012)

Deep Learning of Representations for Unsupervised and Transfer Learning. - Yoshua Bengio (ICML Unsupervised and Transfer Learning, 2012)

Random Search for Hyper-Parameter Optimization. - James Bergstra; Yoshua Bengio (J. Mach. Learn. Res., 2012)

Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing. - Antoine Bordes; Xavier Glorot; Jason Weston; Yoshua Bengio (AISTATS, 2012)

Learning Algorithms for the Classification Restricted Boltzmann Machine. - Hugo Larochelle; Michael I. Mandel; Razvan Pascanu; Yoshua Bengio (J. Mach. Learn. Res., 2012)

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. - Grégoire Mesnil; Yann N. Dauphin; Xavier Glorot; Salah Rifai; Yoshua Bengio; Ian J. Goodfellow; Erick Lavoie; Xavier Muller; Guillaume Desjardins; David Warde-Farley; Pascal Vincent; Aaron C. Courville; et al. (ICML Unsupervised and Transfer Learning, 2012)

Beyond Skill Rating: Advanced Matchmaking in Ghost Recon Online. - Olivier Delalleau; Emile Contal; Eric Thibodeau-Laufer; Raul Chandias Ferrari; Yoshua Bengio; Frank Zhang (IEEE Trans. Comput. Intell. AI Games, 2012)

Practical Recommendations for Gradient-Based Training of Deep Architectures. - Yoshua Bengio (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions. - Heng Luo; Pierre Luc Carrier; Aaron C. Courville; Yoshua Bengio (AISTATS, 2013)

Stacked calibration of off-policy policy evaluation for video game matchmaking. - Eric Thibodeau-Laufer; Raul Chandias Ferrari; Li Yao; Olivier Delalleau; Yoshua Bengio (CIG, 2013)

Advances in optimizing recurrent networks. - Yoshua Bengio; Nicolas Boulanger-Lewandowski; Razvan Pascanu (ICASSP, 2013)

High-dimensional sequence transduction. - Nicolas Boulanger-Lewandowski; Yoshua Bengio; Pascal Vincent (ICASSP, 2013)

Combining modality specific deep neural networks for emotion recognition in video. - Samira Ebrahimi Kahou; Christopher J. Pal; Xavier Bouthillier; Pierre Froumenty; Çaglar Gülçehre; Roland Memisevic; Pascal Vincent; Aaron C. Courville; Yoshua Bengio; Raul Chandias Ferrari; Mehdi Mirza; Sébastien Jean; et al. (ICMI, 2013)

Better Mixing via Deep Representations. - Yoshua Bengio; Grégoire Mesnil; Yann N. Dauphin; Salah Rifai (ICML (1), 2013)

Maxout Networks. - Ian J. Goodfellow; David Warde-Farley; Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (ICML (3), 2013)

On the difficulty of training recurrent neural networks. - Razvan Pascanu; Tomás Mikolov; Yoshua Bengio (ICML (3), 2013)

Challenges in Representation Learning: A Report on Three Machine Learning Contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (ICONIP (3), 2013)

Unsupervised and Transfer Learning under Uncertainty - From Object Detections to Scene Categorization. - Grégoire Mesnil; Salah Rifai; Antoine Bordes; Xavier Glorot; Yoshua Bengio; Pascal Vincent (ICPRAM, 2013)

Unsupervised Learning of Semantics of Object Detections for Scene Categorization. - Grégoire Mesnil; Salah Rifai; Antoine Bordes; Xavier Glorot; Yoshua Bengio; Pascal Vincent (ICPRAM (Selected Papers), 2013)

Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding. - Grégoire Mesnil; Xiaodong He 001; Li Deng 001; Yoshua Bengio (INTERSPEECH, 2013)

Audio Chord Recognition with Recurrent Neural Networks. - Nicolas Boulanger-Lewandowski; Yoshua Bengio; Pascal Vincent (ISMIR, 2013)

Generalized Denoising Auto-Encoders as Generative Models. - Yoshua Bengio; Li Yao; Guillaume Alain; Pascal Vincent (NIPS, 2013)

Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs. - Yann N. Dauphin; Yoshua Bengio (NIPS, 2013)

Multi-Prediction Deep Boltzmann Machines. - Ian J. Goodfellow; Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (NIPS, 2013)

Modeling term dependencies with quantum language models for IR. - Alessandro Sordoni; Jian-Yun Nie; Yoshua Bengio (SIGIR, 2013)

Deep Learning of Representations: Looking Forward. - Yoshua Bengio (SLSP, 2013)

Learning Deep Physiological Models of Affect. - Héctor Pérez Martínez; Yoshua Bengio; Georgios N. Yannakakis (IEEE Comput. Intell. Mag., 2013)

Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation. - Yoshua Bengio; Nicholas Léonard; Aaron C. Courville (CoRR, 2013)

Deep Generative Stochastic Networks Trainable by Backprop. - Yoshua Bengio; Eric Thibodeau-Laufer; Jason Yosinski (CoRR, 2013)

Pylearn2: a machine learning research library. - Ian J. Goodfellow; David Warde-Farley; Pascal Lamblin; Vincent Dumoulin; Mehdi Mirza; Razvan Pascanu; James Bergstra; Frédéric Bastien; Yoshua Bengio (CoRR, 2013)

Learned-norm pooling for deep neural networks. - Çaglar Gülçehre; Kyunghyun Cho; Razvan Pascanu; Yoshua Bengio (CoRR, 2013)

Regularized Auto-Encoders Estimate Local Statistics - Guillaume Alain; Yoshua Bengio; Salah Rifai (ICLR, 2013)

A Semantic Matching Energy Function for Learning with Multi-relational Data - Xavier Glorot; Antoine Bordes; Jason Weston; Yoshua Bengio (ICLR (Workshop Poster), 2013)

Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines - Guillaume Desjardins; Razvan Pascanu; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2013)

Joint Training Deep Boltzmann Machines for Classification - Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (ICLR (Workshop), 2013)

Big Neural Networks Waste Capacity - Yann N. Dauphin; Yoshua Bengio (ICLR (Workshop), 2013)

Natural Gradient Revisited - Razvan Pascanu; Yoshua Bengio (ICLR (Workshop Poster), 2013)

Knowledge Matters: Importance of Prior Information for Optimization - Çaglar Gülçehre; Yoshua Bengio (ICLR, 2013)

Estimating or Propagating Gradients Through Stochastic Neurons - Yoshua Bengio (CoRR, 2013)

Representation Learning: A Review and New Perspectives. - Yoshua Bengio; Aaron C. Courville; Pascal Vincent (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Scaling Up Spike-and-Slab Models for Unsupervised Feature Learning. - Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Deep Learning of Representations. - Yoshua Bengio; Aaron C. Courville (Handbook on Neural Information Processing, 2013)

On the Challenges of Physical Implementations of RBMs. - Vincent Dumoulin; Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (AAAI, 2014)

Learning Concept Embeddings for Query Expansion by Quantum Entropy Minimization. - Alessandro Sordoni; Yoshua Bengio; Jian-Yun Nie (AAAI, 2014)

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. - Kyunghyun Cho; Bart van Merrienboer; Çaglar Gülçehre; Dzmitry Bahdanau; Fethi Bougares; Holger Schwenk; Yoshua Bengio (EMNLP, 2014)

Deep learning and cultural evolution. - Yoshua Bengio (GECCO (Companion), 2014)

Deep Generative Stochastic Networks Trainable by Backprop. - Yoshua Bengio; Eric Laufer; Guillaume Alain; Jason Yosinski (ICML, 2014)

Marginalized Denoising Auto-encoders for Nonlinear Representations. - Minmin Chen; Kilian Q. Weinberger; Fei Sha; Yoshua Bengio (ICML, 2014)

Scaling up deep learning. - Yoshua Bengio (KDD, 2014)

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. - Yann N. Dauphin; Razvan Pascanu; Çaglar Gülçehre; KyungHyun Cho; Surya Ganguli; Yoshua Bengio (NIPS, 2014)

Generative Adversarial Nets. - Ian J. Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron C. Courville; Yoshua Bengio (NIPS, 2014)

On the Number of Linear Regions of Deep Neural Networks. - Guido Montúfar; Razvan Pascanu; KyungHyun Cho; Yoshua Bengio (NIPS, 2014)

Iterative Neural Autoregressive Distribution Estimator NADE-k. - Tapani Raiko; Li Yao; KyungHyun Cho; Yoshua Bengio (NIPS, 2014)

How transferable are features in deep neural networks? - Jason Yosinski; Jeff Clune; Yoshua Bengio; Hod Lipson (NIPS, 2014)

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. - Çaglar Gülçehre; KyungHyun Cho; Razvan Pascanu; Yoshua Bengio (ECML/PKDD (1), 2014)

On the Equivalence between Deep NADE and Generative Stochastic Networks. - Li Yao; Sherjil Ozair; KyungHyun Cho; Yoshua Bengio (ECML/PKDD (3), 2014)

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches. - Kyunghyun Cho; Bart van Merrienboer; Dzmitry Bahdanau; Yoshua Bengio (SSST@EMNLP, 2014)

Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation. - Jean Pouget-Abadie; Dzmitry Bahdanau; Bart van Merrienboer; Kyunghyun Cho; Yoshua Bengio (SSST@EMNLP, 2014)

Conditioning and time representation in long short-term memory networks. - François Rivest; John Kalaska; Yoshua Bengio (Biol. Cybern., 2014)

How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation. - Yoshua Bengio (CoRR, 2014)

Bounding the Test Log-Likelihood of Generative Models. - Yoshua Bengio; Li Yao (ICLR (Poster), 2014)

Exponentially Increasing the Capacity-to-Computation Ratio for Conditional Computation in Deep Learning. - Kyunghyun Cho; Yoshua Bengio (CoRR, 2014)

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. - Kyunghyun Cho; Bart van Merrienboer; Çaglar Gülçehre; Fethi Bougares; Holger Schwenk; Yoshua Bengio (CoRR, 2014)

End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results. - Jan Chorowski; Dzmitry Bahdanau; Kyunghyun Cho; Yoshua Bengio (CoRR, 2014)

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. - Junyoung Chung; Çaglar Gülçehre; KyungHyun Cho; Yoshua Bengio (CoRR, 2014)

Deep Tempering. - Guillaume Desjardins; Heng Luo; Aaron C. Courville; Yoshua Bengio (CoRR, 2014)

An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks. - Ian J. Goodfellow; Mehdi Mirza; Xia Da; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2014)

ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient. - Çaglar Gülçehre; Yoshua Bengio (CoRR, 2014)

Not All Neural Embeddings are Born Equal. - Felix Hill; KyungHyun Cho; Sébastien Jean; Coline Devin; Yoshua Bengio (CoRR, 2014)

Deep Directed Generative Autoencoders. - Sherjil Ozair; Yoshua Bengio (CoRR, 2014)

Multimodal Transitions for Generative Stochastic Networks. - Sherjil Ozair; Li Yao; Yoshua Bengio (ICLR (Workshop Poster), 2014)

On the saddle point problem for non-convex optimization. - Razvan Pascanu; Yann N. Dauphin; Surya Ganguli; Yoshua Bengio (CoRR, 2014)

How to Construct Deep Recurrent Neural Networks. - Razvan Pascanu; Çaglar Gülçehre; Kyunghyun Cho; Yoshua Bengio (ICLR (Poster), 2014)

On the number of inference regions of deep feed forward networks with piece-wise linear activations. - Razvan Pascanu; Guido Montúfar; Yoshua Bengio (ICLR (Poster), 2014)

An empirical analysis of dropout in piecewise linear networks. - David Warde-Farley; Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2014)

Revisiting Natural Gradient for Deep Networks - Razvan Pascanu; Yoshua Bengio (ICLR, 2014)

What regularized auto-encoders learn from the data-generating distribution. - Guillaume Alain; Yoshua Bengio (J. Mach. Learn. Res., 2014)

A semantic matching energy function for learning with multi-relational data - Application to word-sense disambiguation. - Antoine Bordes; Xavier Glorot; Jason Weston; Yoshua Bengio (Mach. Learn., 2014)

Learning semantic representations of objects and their parts. - Grégoire Mesnil; Antoine Bordes; Jason Weston; Gal Chechik; Yoshua Bengio (Mach. Learn., 2014)

The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. - Aaron C. Courville; Guillaume Desjardins; James Bergstra; Yoshua Bengio (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Evolving Culture Versus Local Minima. - Yoshua Bengio (Growing Adaptive Machines, 2014)

On Using Very Large Target Vocabulary for Neural Machine Translation. - Sébastien Jean; KyungHyun Cho; Roland Memisevic; Yoshua Bengio (ACL (1), 2015)

IAPR keynote lecture IV: Deep learning. - Yoshua Bengio (ACPR, 2015)

A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion. - Alessandro Sordoni; Yoshua Bengio; Hossein Vahabi; Christina Lioma; Jakob Grue Simonsen; Jian-Yun Nie (CIKM, 2015)

Gated Feedback Recurrent Neural Networks. - Junyoung Chung; Çaglar Gülçehre; Kyunghyun Cho; Yoshua Bengio (ICML, 2015)

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments. - Stephan Gouws; Yoshua Bengio; Greg Corrado (ICML, 2015)

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. - Kelvin Xu; Jimmy Ba; Ryan Kiros; Kyunghyun Cho; Aaron C. Courville; Ruslan Salakhutdinov; Richard S. Zemel; Yoshua Bengio (ICML, 2015)

Attention-Based Models for Speech Recognition. - Jan Chorowski; Dzmitry Bahdanau; Dmitriy Serdyuk; Kyunghyun Cho; Yoshua Bengio (NIPS, 2015)

A Recurrent Latent Variable Model for Sequential Data. - Junyoung Chung; Kyle Kastner; Laurent Dinh; Kratarth Goel; Aaron C. Courville; Yoshua Bengio (NIPS, 2015)

BinaryConnect: Training Deep Neural Networks with binary weights during propagations. - Matthieu Courbariaux; Yoshua Bengio; Jean-Pierre David (NIPS, 2015)

Equilibrated adaptive learning rates for non-convex optimization. - Yann N. Dauphin; Harm de Vries; Yoshua Bengio (NIPS, 2015)

Artificial Neural Networks Applied to Taxi Destination Prediction. - Alexandre de Brébisson; Étienne Simon; Alex Auvolat; Pascal Vincent; Yoshua Bengio (DC@PKDD/ECML, 2015)

Difference Target Propagation. - Dong-Hyun Lee; Saizheng Zhang; Asja Fischer; Yoshua Bengio (ECML/PKDD (1), 2015)

Montreal Neural Machine Translation Systems for WMT'15. - Sébastien Jean; Orhan Firat; Kyunghyun Cho; Roland Memisevic; Yoshua Bengio (WMT@EMNLP, 2015)

GSNs : Generative Stochastic Networks. - Guillaume Alain; Yoshua Bengio; Li Yao; Jason Yosinski; Eric Thibodeau-Laufer; Saizheng Zhang; Pascal Vincent (CoRR, 2015)

Variance Reduction in SGD by Distributed Importance Sampling. - Guillaume Alain; Alex Lamb; Chinnadhurai Sankar; Aaron C. Courville; Yoshua Bengio (CoRR, 2015)

Neural Machine Translation by Jointly Learning to Align and Translate. - Dzmitry Bahdanau; Kyunghyun Cho; Yoshua Bengio (ICLR, 2015)

Task Loss Estimation for Sequence Prediction. - Dzmitry Bahdanau; Dmitriy Serdyuk; Philemon Brakel; Nan Rosemary Ke; Jan Chorowski; Aaron C. Courville; Yoshua Bengio (CoRR, 2015)

Early Inference in Energy-Based Models Approximates Back-Propagation. - Yoshua Bengio (CoRR, 2015)

Towards Biologically Plausible Deep Learning. - Yoshua Bengio; Dong-Hyun Lee; Jörg Bornschein; Zhouhan Lin (CoRR, 2015)

An objective function for STDP. - Yoshua Bengio; Thomas Mesnard; Asja Fischer; Saizheng Zhang; Yuhai Wu (CoRR, 2015)

Reweighted Wake-Sleep. - Jörg Bornschein; Yoshua Bengio (ICLR, 2015)

Training opposing directed models using geometric mean matching. - Jörg Bornschein; Samira Shabanian; Asja Fischer; Yoshua Bengio (CoRR, 2015)

Low precision arithmetic for deep learning. - Matthieu Courbariaux; Yoshua Bengio; Jean-Pierre David (ICLR (Workshop), 2015)

RMSProp and equilibrated adaptive learning rates for non-convex optimization. - Yann N. Dauphin; Harm de Vries; Junyoung Chung; Yoshua Bengio (CoRR, 2015)

NICE: Non-linear Independent Components Estimation. - Laurent Dinh; David Krueger 001; Yoshua Bengio (ICLR (Workshop), 2015)

On Using Monolingual Corpora in Neural Machine Translation. - Çaglar Gülçehre; Orhan Firat; Kelvin Xu; Kyunghyun Cho; Loïc Barrault; Huei-Chi Lin; Fethi Bougares; Holger Schwenk; Yoshua Bengio (CoRR, 2015)

Embedding Word Similarity with Neural Machine Translation. - Felix Hill; Kyunghyun Cho; Sébastien Jean; Coline Devin; Yoshua Bengio (ICLR (Workshop), 2015)

Target Propagation. - Dong-Hyun Lee; Saizheng Zhang; Antoine Biard; Yoshua Bengio (ICLR (Workshop), 2015)

Blocks and Fuel: Frameworks for deep learning. - Bart van Merriënboer; Dzmitry Bahdanau; Vincent Dumoulin; Dmitriy Serdyuk; David Warde-Farley; Jan Chorowski; Yoshua Bengio (CoRR, 2015)

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews. - Grégoire Mesnil; Tomás Mikolov; Marc'Aurelio Ranzato; Yoshua Bengio (ICLR (Workshop), 2015)

FitNets: Hints for Thin Deep Nets. - Adriana Romero; Nicolas Ballas; Samira Ebrahimi Kahou; Antoine Chassang; Carlo Gatta; Yoshua Bengio (ICLR (Poster), 2015)

Hierarchical Neural Network Generative Models for Movie Dialogues. - Iulian Vlad Serban; Alessandro Sordoni; Yoshua Bengio; Aaron C. Courville; Joelle Pineau (CoRR, 2015)

ReSeg: A Recurrent Neural Network for Object Segmentation. - Francesco Visin; Kyle Kastner; Aaron C. Courville; Yoshua Bengio; Matteo Matteucci; KyungHyun Cho (CoRR, 2015)

ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks. - Francesco Visin; Kyle Kastner; Kyunghyun Cho; Matteo Matteucci; Aaron C. Courville; Yoshua Bengio (CoRR, 2015)

Trainable performance upper bounds for image and video captioning. - Li Yao; Nicolas Ballas; KyungHyun Cho; John R. Smith; Yoshua Bengio (CoRR, 2015)

Deep learning. - Yann LeCun; Yoshua Bengio; Geoffrey E. Hinton (Nat., 2015)

Editorial introduction to the Neural Networks special issue on Deep Learning of Representations. - Yoshua Bengio; Honglak Lee (Neural Networks, 2015)

Challenges in representation learning: A report on three machine learning contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (Neural Networks, 2015)

Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding. - Grégoire Mesnil; Yann N. Dauphin; Kaisheng Yao; Yoshua Bengio; Li Deng 001; Dilek Hakkani-Tür; Xiaodong He 001; Larry P. Heck; Gökhan Tür; Dong Yu 001; Geoffrey Zweig (IEEE ACM Trans. Audio Speech Lang. Process., 2015)

Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks. - Kyunghyun Cho; Aaron C. Courville; Yoshua Bengio (IEEE Trans. Multim., 2015)

Deep Learning. - Ian J. Goodfellow; Yoshua Bengio; Aaron C. Courville (MIT Press, 2016)

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models. - Iulian Vlad Serban; Alessandro Sordoni; Yoshua Bengio; Aaron C. Courville; Joelle Pineau (AAAI, 2016)

A Character-level Decoder without Explicit Segmentation for Neural Machine Translation. - Junyoung Chung; Kyunghyun Cho; Yoshua Bengio (ACL (1), 2016)

Pointing the Unknown Words. - Çaglar Gülçehre; Sungjin Ahn; Ramesh Nallapati; Bowen Zhou 002; Yoshua Bengio (ACL (1), 2016)

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. - Iulian Vlad Serban; Alberto García-Durán; Çaglar Gülçehre; Sungjin Ahn; Sarath Chandar; Aaron C. Courville; Yoshua Bengio (ACL (1), 2016)

Oracle Performance for Visual Captioning. - Li Yao; Nicolas Ballas; Kyunghyun Cho; John R. Smith; Yoshua Bengio (BMVC, 2016)

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation. - Francesco Visin; Adriana Romero; Kyunghyun Cho; Matteo Matteucci; Marco Ciccone; Kyle Kastner; Yoshua Bengio; Aaron C. Courville (CVPR Workshops, 2016)

End-to-end attention-based large vocabulary speech recognition. - Dzmitry Bahdanau; Jan Chorowski; Dmitriy Serdyuk; Philemon Brakel; Yoshua Bengio (ICASSP, 2016)

Batch normalized recurrent neural networks. - César Laurent; Gabriel Pereyra; Philemon Brakel; Ying Zhang 033; Yoshua Bengio (ICASSP, 2016)

Unitary Evolution Recurrent Neural Networks. - Martín Arjovsky; Amar Shah 001; Yoshua Bengio (ICML, 2016)

Bidirectional Helmholtz Machines. - Jörg Bornschein; Samira Shabanian; Asja Fischer; Yoshua Bengio (ICML, 2016)

Noisy Activation Functions. - Çaglar Gülçehre; Marcin Moczulski; Misha Denil; Yoshua Bengio (ICML, 2016)

Deconstructing the Ladder Network Architecture. - Mohammad Pezeshki; Linxi Fan; Philemon Brakel; Aaron C. Courville; Yoshua Bengio (ICML, 2016)

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks. - Ying Zhang 033; Mohammad Pezeshki; Philémon Brakel; Saizheng Zhang; César Laurent; Yoshua Bengio; Aaron C. Courville (INTERSPEECH, 2016)

HeMIS: Hetero-Modal Image Segmentation. - Mohammad Havaei; Nicolas Guizard; Nicolas Chapados; Yoshua Bengio (MICCAI (2), 2016)

Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism. - Orhan Firat; Kyunghyun Cho; Yoshua Bengio (HLT-NAACL, 2016)

Professor Forcing: A New Algorithm for Training Recurrent Networks. - Anirudh Goyal; Alex Lamb; Ying Zhang 033; Saizheng Zhang; Aaron C. Courville; Yoshua Bengio (NIPS, 2016)

Binarized Neural Networks. - Itay Hubara; Matthieu Courbariaux; Daniel Soudry; Ran El-Yaniv; Yoshua Bengio (NIPS, 2016)

On Multiplicative Integration with Recurrent Neural Networks. - Yuhuai Wu; Saizheng Zhang; Ying Zhang 033; Yoshua Bengio; Ruslan Salakhutdinov (NIPS, 2016)

Architectural Complexity Measures of Recurrent Neural Networks. - Saizheng Zhang; Yuhuai Wu; Tong Che; Zhouhan Lin; Roland Memisevic; Ruslan Salakhutdinov; Yoshua Bengio (NIPS, 2016)

Batch-normalized joint training for DNN-based distant speech recognition. - Mirco Ravanelli; Philemon Brakel; Maurizio Omologo; Yoshua Bengio (SLT, 2016)

NYU-MILA Neural Machine Translation Systems for WMT'16. - Junyoung Chung; Kyunghyun Cho; Yoshua Bengio (WMT, 2016)

A Neural Knowledge Language Model. - Sungjin Ahn; Heeyoul Choi; Tanel Pärnamaa; Yoshua Bengio (CoRR, 2016)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible. - Yoshua Bengio; Benjamin Scellier; Olexa Bilaniuk; João Sacramento; Walter Senn (CoRR, 2016)

Hierarchical Memory Networks. - Sarath Chandar; Sungjin Ahn; Hugo Larochelle; Pascal Vincent; Gerald Tesauro; Yoshua Bengio (CoRR, 2016)

BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. - Matthieu Courbariaux; Yoshua Bengio (CoRR, 2016)

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (CoRR, 2016)

Deep Directed Generative Models with Energy-Based Probability Estimation. - Taesup Kim; Yoshua Bengio (CoRR, 2016)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Aaron C. Courville; Chris Pal (CoRR, 2016)

Neural Networks with Few Multiplications. - Zhouhan Lin; Matthieu Courbariaux; Roland Memisevic; Yoshua Bengio (ICLR, 2016)

On Random Weights for Texture Generation in One Layer Neural Networks. - Mihir Mongia; Kundan Kumar; Akram Erraqabi; Yoshua Bengio (CoRR, 2016)

Recurrent Neural Networks With Limited Numerical Precision. - Joachim Ott; Zhouhan Lin; Ying Zhang 033; Shih-Chii Liu; Yoshua Bengio (CoRR, 2016)

Diet Networks: Thin Parameters for Fat Genomic. - Adriana Romero; Pierre Luc Carrier; Akram Erraqabi; Tristan Sylvain; Alex Auvolat; Etienne Dejoie; Marc-André Legault; Marie-Pierre Dubé; Julie G. Hussin; Yoshua Bengio (CoRR, 2016)

Towards a Biologically Plausible Backprop. - Benjamin Scellier; Yoshua Bengio (CoRR, 2016)

Invariant Representations for Noisy Speech Recognition. - Dmitriy Serdyuk; Kartik Audhkhasi; Philemon Brakel; Bhuvana Ramabhadran; Samuel Thomas 001; Yoshua Bengio (CoRR, 2016)

Iterative Alternating Neural Attention for Machine Reading. - Alessandro Sordoni; Philip Bachman; Yoshua Bengio (CoRR, 2016)

EmoNets: Multimodal deep learning approaches for emotion recognition in video. - Samira Ebrahimi Kahou; Xavier Bouthillier; Pascal Lamblin; Çaglar Gülçehre; Vincent Michalski; Kishore Konda; Sébastien Jean; Pierre Froumenty; Yann N. Dauphin; Nicolas Boulanger-Lewandowski; Raul Chandias Ferrari; Mehdi Mirza; et al. (J. Multimodal User Interfaces, 2016)

Big Data: Theoretical Aspects [Scanning the Issue]. - Simon Haykin 001; Stephen J. Wright 001; Yoshua Bengio (Proc. IEEE, 2016)

Learning to Understand Phrases by Embedding the Dictionary. - Felix Hill; KyungHyun Cho; Anna Korhonen; Yoshua Bengio (Trans. Assoc. Comput. Linguistics, 2016)

Denoising Criterion for Variational Auto-Encoding Framework. - Daniel Jiwoong Im; Sungjin Ahn; Roland Memisevic; Yoshua Bengio (AAAI, 2017)

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. - Iulian Vlad Serban; Tim Klinger; Gerald Tesauro; Kartik Talamadupula; Bowen Zhou 002; Yoshua Bengio; Aaron C. Courville (AAAI, 2017)

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. - Iulian Vlad Serban; Alessandro Sordoni; Ryan Lowe; Laurent Charlin; Joelle Pineau; Aaron C. Courville; Yoshua Bengio (AAAI, 2017)

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation. - Simon Jégou; Michal Drozdzal; David Vázquez 001; Adriana Romero; Yoshua Bengio (CVPR Workshops, 2017)

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space. - Anh Nguyen 002; Jeff Clune; Yoshua Bengio; Alexey Dosovitskiy; Jason Yosinski (CVPR, 2017)

On random weights for texture generation in one layer CNNS. - Mihir Mongia; Kundan Kumar; Akram Erraqabi; Yoshua Bengio (ICASSP, 2017)

A network of deep neural networks for Distant Speech Recognition. - Mirco Ravanelli; Philemon Brakel; Maurizio Omologo; Yoshua Bengio (ICASSP, 2017)

Count-ception: Counting by Fully Convolutional Redundant Counting. - Joseph Paul Cohen; Geneviève Boucher; Craig A. Glastonbury; Henry Z. Lo; Yoshua Bengio (ICCV Workshops, 2017)

Understanding intermediate layers using linear classifier probes. - Guillaume Alain; Yoshua Bengio (ICLR (Workshop), 2017)

An Actor-Critic Algorithm for Sequence Prediction. - Dzmitry Bahdanau; Philemon Brakel; Kelvin Xu; Anirudh Goyal; Ryan Lowe; Joelle Pineau; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2017)

Mode Regularized Generative Adversarial Networks. - Tong Che; Yanran Li; Athul Paul Jacob; Yoshua Bengio; Wenjie Li 002 (ICLR (Poster), 2017)

Hierarchical Multiscale Recurrent Neural Networks. - Junyoung Chung; Sungjin Ahn; Yoshua Bengio (ICLR (Poster), 2017)

Mollifying Networks. - Çaglar Gülçehre; Marcin Moczulski; Francesco Visin; Yoshua Bengio (ICLR (Poster), 2017)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Aaron C. Courville; Christopher J. Pal (ICLR (Poster), 2017)

A Structured Self-Attentive Sentence Embedding. - Zhouhan Lin; Minwei Feng; Cícero Nogueira dos Santos; Mo Yu; Bing Xiang; Bowen Zhou 002; Yoshua Bengio (ICLR (Poster), 2017)

Towards an automatic Turing test: Learning to evaluate dialogue responses. - Ryan Lowe; Michael Noseworthy; Iulian Vlad Serban; Nicolas Angelard-Gontier; Yoshua Bengio; Joelle Pineau (ICLR (Workshop), 2017)

SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. - Soroush Mehri; Kundan Kumar; Ishaan Gulrajani; Rithesh Kumar; Shubham Jain; Jose Sotelo; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2017)

Generalizable Features From Unsupervised Learning. - Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (ICLR (Workshop), 2017)

Diet Networks: Thin Parameters for Fat Genomics. - Adriana Romero; Pierre Luc Carrier; Akram Erraqabi; Tristan Sylvain; Alex Auvolat; Etienne Dejoie; Marc-André Legault; Marie-Pierre Dubé; Julie G. Hussin; Yoshua Bengio (ICLR (Poster), 2017)

Char2Wav: End-to-End Speech Synthesis. - Jose Sotelo; Soroush Mehri; Kundan Kumar; João Felipe Santos; Kyle Kastner; Aaron C. Courville; Yoshua Bengio (ICLR (Workshop), 2017)

Improving Generative Adversarial Networks with Denoising Feature Matching. - David Warde-Farley; Yoshua Bengio (ICLR (Poster), 2017)

A Closer Look at Memorization in Deep Networks. - Devansh Arpit; Stanislaw Jastrzebski; Nicolas Ballas; David Krueger 001; Emmanuel Bengio; Maxinder S. Kanwal; Tegan Maharaj; Asja Fischer; Aaron C. Courville; Yoshua Bengio; Simon Lacoste-Julien (ICML, 2017)

Sharp Minima Can Generalize For Deep Nets. - Laurent Dinh; Razvan Pascanu; Samy Bengio; Yoshua Bengio (ICML, 2017)

A robust adaptive stochastic gradient method for deep learning. - Çaglar Gülçehre; Jose Sotelo; Marcin Moczulski; Yoshua Bengio (IJCNN, 2017)

Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition. - Taesup Kim; Inchul Song; Yoshua Bengio (INTERSPEECH, 2017)

Improving Speech Recognition by Revising Gated Recurrent Units. - Mirco Ravanelli; Philemon Brakel; Maurizio Omologo; Yoshua Bengio (INTERSPEECH, 2017)

Towards more hardware-friendly deep learning. - Yoshua Bengio (TIML@ISCA, 2017)

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. - Anirudh Goyal; Nan Rosemary Ke; Surya Ganguli; Yoshua Bengio (NIPS, 2017)

Z-Forcing: Training Stochastic Recurrent Networks. - Anirudh Goyal; Alessandro Sordoni; Marc-Alexandre Côté; Nan Rosemary Ke; Yoshua Bengio (NIPS, 2017)

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (NIPS, 2017)

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. - Alex Lamb; R. Devon Hjelm; Yaroslav Ganin; Joseph Paul Cohen; Aaron C. Courville; Yoshua Bengio (NIPS, 2017)

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (Rep4NLP@ACL, 2017)

Learning to Compute Word Embeddings On the Fly. - Dzmitry Bahdanau; Tom Bosc; Stanislaw Jastrzebski; Edward Grefenstette; Pascal Vincent; Yoshua Bengio (CoRR, 2017)

Independently Controllable Features. - Emmanuel Bengio; Valentin Thomas; Joelle Pineau; Doina Precup; Yoshua Bengio (CoRR, 2017)

Maximum-Likelihood Augmented Discrete Generative Adversarial Networks. - Tong Che; Yanran Li; Ruixiang Zhang; R. Devon Hjelm; Wenjie Li 002; Yangqiu Song; Yoshua Bengio (CoRR, 2017)

Count-ception: Counting by Fully Convolutional Redundant Counting. - Joseph Paul Cohen; Henry Z. Lo; Yoshua Bengio (CoRR, 2017)

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation. - Michal Drozdzal; Gabriel Chartrand; Eugene Vorontsov; Lisa Di-Jorio; An Tang; Adriana Romero; Yoshua Bengio; Chris Pal; Samuel Kadoury (CoRR, 2017)

Memory Augmented Neural Networks with Wormhole Connections. - Çaglar Gülçehre; Sarath Chandar; Yoshua Bengio (CoRR, 2017)

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (CoRR, 2017)

Boundary-Seeking Generative Adversarial Networks. - R. Devon Hjelm; Athul Paul Jacob; Tong Che; Kyunghyun Cho; Yoshua Bengio (CoRR, 2017)

Deep Learning for Patient-Specific Kidney Graft Survival Analysis. - Margaux Luck; Tristan Sylvain; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (CoRR, 2017)

Multiscale sequence modeling with a learned dictionary. - Bart van Merriënboer; Amartya Sanyal; Hugo Larochelle; Yoshua Bengio (CoRR, 2017)

Image Segmentation by Iterative Inference from Conditional Score Estimation. - Adriana Romero; Michal Drozdzal; Akram Erraqabi; Simon Jégou; Yoshua Bengio (CoRR, 2017)

Deep Complex Networks. - Chiheb Trabelsi; Olexa Bilaniuk; Dmitriy Serdyuk; Sandeep Subramanian; João Felipe Santos; Soroush Mehri; Negar Rostamzadeh; Yoshua Bengio; Christopher J. Pal (CoRR, 2017)

Independently Controllable Factors. - Valentin Thomas; Jules Pondard; Emmanuel Bengio; Marc Sarfati; Philippe Beaudoin; Marie-Jean Meurs; Joelle Pineau; Doina Precup; Yoshua Bengio (CoRR, 2017)

Twin Networks: Using the Future as a Regularizer. - Dmitriy Serdyuk; Nan Rosemary Ke; Alessandro Sordoni; Chris Pal; Yoshua Bengio (CoRR, 2017)

A Deep Reinforcement Learning Chatbot. - Iulian Vlad Serban; Chinnadhurai Sankar; Mathieu Germain; Saizheng Zhang; Zhouhan Lin; Sandeep Subramanian; Taesup Kim; Michael Pieper; Sarath Chandar; Nan Rosemary Ke; Sai Mudumba; Alexandre de Brébisson; et al. (CoRR, 2017)

The Consciousness Prior. - Yoshua Bengio (CoRR, 2017)

Generalization in Deep Learning. - Kenji Kawaguchi; Leslie Pack Kaelbling; Yoshua Bengio (CoRR, 2017)

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks. - Nan Rosemary Ke; Anirudh Goyal; Olexa Bilaniuk; Jonathan Binas; Laurent Charlin; Chris Pal; Yoshua Bengio (CoRR, 2017)

Three Factors Influencing Minima in SGD. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (CoRR, 2017)

ACtuAL: Actor-Critic Under Adversarial Learning. - Anirudh Goyal; Nan Rosemary Ke; Alex Lamb; R. Devon Hjelm; Chris Pal; Joelle Pineau; Yoshua Bengio (CoRR, 2017)

Variational Bi-LSTMs. - Samira Shabanian; Devansh Arpit; Adam Trischler; Yoshua Bengio (CoRR, 2017)

Measuring the tendency of CNNs to Learn Surface Statistical Regularities. - Jason Jo; Yoshua Bengio (CoRR, 2017)

Context-dependent word representation for neural machine translation. - Heeyoul Choi; Kyunghyun Cho; Yoshua Bengio (Comput. Speech Lang., 2017)

Multi-way, multilingual neural machine translation. - Orhan Firat; Kyunghyun Cho; Baskaran Sankaran; Fatos T. Yarman-Vural; Yoshua Bengio (Comput. Speech Lang., 2017)

On integrating a language model into neural machine translation. - Çaglar Gülçehre; Orhan Firat; Kelvin Xu; Kyunghyun Cho; Yoshua Bengio (Comput. Speech Lang., 2017)

Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation. - Benjamin Scellier; Yoshua Bengio (Frontiers Comput. Neurosci., 2017)

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations. - Itay Hubara; Matthieu Courbariaux; Daniel Soudry; Ran El-Yaniv; Yoshua Bengio (J. Mach. Learn. Res., 2017)

Brain tumor segmentation with Deep Neural Networks. - Mohammad Havaei; Axel Davy; David Warde-Farley; Antoine Biard; Aaron C. Courville; Yoshua Bengio; Chris Pal; Pierre-Marc Jodoin; Hugo Larochelle (Medical Image Anal., 2017)

The representational geometry of word meanings acquired by neural machine translation models. - Felix Hill; Kyunghyun Cho; Sébastien Jean; Yoshua Bengio (Mach. Transl., 2017)

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model. - Yoshua Bengio; Thomas Mesnard; Asja Fischer; Saizheng Zhang; Yuhuai Wu (Neural Comput., 2017)

Online and offline handwritten Chinese character recognition: A comprehensive study and new benchmark. - Xu-Yao Zhang; Yoshua Bengio; Cheng-Lin Liu 001 (Pattern Recognit., 2017)

End-to-End Online Writer Identification With Recurrent Neural Network. - Xu-Yao Zhang; Guo-Sen Xie; Cheng-Lin Liu 001; Yoshua Bengio (IEEE Trans. Hum. Mach. Syst., 2017)

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. - Yikang Shen; Zhouhan Lin; Athul Paul Jacob; Alessandro Sordoni; Aaron C. Courville; Yoshua Bengio (ACL (1), 2018)

Neural Models for Key Phrase Extraction and Question Generation. - Sandeep Subramanian; Tong Wang 012; Xingdi Yuan; Saizheng Zhang; Adam Trischler; Yoshua Bengio (QA@ACL, 2018)

On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation. - Arantxa Casanova; Guillem Cucurull; Michal Drozdzal; Adriana Romero; Yoshua Bengio (CVPR Workshops, 2018)

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. - Zhilin Yang 001; Peng Qi 003; Saizheng Zhang; Yoshua Bengio; William W. Cohen; Ruslan Salakhutdinov; Christopher D. Manning (EMNLP, 2018)

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICANN (3), 2018)

Monaural Singing Voice Separation with Skip-Filtering Connections and Recurrent Inference of Time-Frequency Mask. - Stylianos Ioannis Mimilakis; Konstantinos Drossos; João Felipe Santos; Gerald Schuller; Tuomas Virtanen; Yoshua Bengio (ICASSP, 2018)

Towards End-to-end Spoken Language Understanding. - Dmitriy Serdyuk; Yongqiang Wang 005; Christian Fuegen; Anuj Kumar; Baiyang Liu; Yoshua Bengio (ICASSP, 2018)

Dynamic Frame Skipping for Fast Speech Recognition in Recurrent Neural Network Based Acoustic Models. - Inchul Song; Junyoung Chung; Taesup Kim; Yoshua Bengio (ICASSP, 2018)

Boundary Seeking GANs. - R. Devon Hjelm; Athul Paul Jacob; Adam Trischler; Gerry Che; Kyunghyun Cho; Yoshua Bengio (ICLR (Poster), 2018)

Residual Connections Encourage Iterative Inference. - Stanislaw Jastrzebski; Devansh Arpit; Nicolas Ballas; Vikas Verma; Tong Che; Yoshua Bengio (ICLR (Poster), 2018)

Finding Flatter Minima with SGD. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICLR (Workshop), 2018)

FigureQA: An Annotated Figure Dataset for Visual Reasoning. - Samira Ebrahimi Kahou; Vincent Michalski; Adam Atkinson; Ákos Kádár; Adam Trischler; Yoshua Bengio (ICLR (Workshop), 2018)

Universal Successor Representations for Transfer Reinforcement Learning. - Chen Ma; Junfeng Wen; Yoshua Bengio (ICLR (Workshop), 2018)

Extending the Framework of Equilibrium Propagation to General Dynamics. - Benjamin Scellier; Anirudh Goyal; Jonathan Binas; Thomas Mesnard; Yoshua Bengio (ICLR (Workshop), 2018)

Twin Networks: Matching the Future for Sequence Generation. - Dmitriy Serdyuk; Nan Rosemary Ke; Alessandro Sordoni; Adam Trischler; Chris Pal; Yoshua Bengio (ICLR (Poster), 2018)

ChatPainter: Improving Text to Image Generation using Dialogue. - Shikhar Sharma 001; Dendi Suhubdy; Vincent Michalski; Samira Ebrahimi Kahou; Yoshua Bengio (ICLR (Workshop), 2018)

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning. - Sandeep Subramanian; Adam Trischler; Yoshua Bengio; Christopher J. Pal (ICLR (Poster), 2018)

Deep Complex Networks. - Chiheb Trabelsi; Olexa Bilaniuk; Ying Zhang 033; Dmitriy Serdyuk; Sandeep Subramanian; João Felipe Santos; Soroush Mehri; Negar Rostamzadeh; Yoshua Bengio; Christopher J. Pal (ICLR (Poster), 2018)

Graph Attention Networks. - Petar Velickovic; Guillem Cucurull; Arantxa Casanova; Adriana Romero; Pietro Liò; Yoshua Bengio (ICLR (Poster), 2018)

Fraternal Dropout. - Konrad Zolna; Devansh Arpit; Dendi Suhubdy; Yoshua Bengio (ICLR (Poster), 2018)

Mutual Information Neural Estimation. - Mohamed Ishmael Belghazi; Aristide Baratin; Sai Rajeswar; Sherjil Ozair; Yoshua Bengio; R. Devon Hjelm; Aaron C. Courville (ICML, 2018)

Focused Hierarchical RNNs for Conditional Sequence Processing. - Nan Rosemary Ke; Konrad Zolna; Alessandro Sordoni; Zhouhan Lin; Adam Trischler; Yoshua Bengio; Joelle Pineau; Laurent Charlin; Christopher J. Pal (ICML, 2018)

MaD TwinNet: Masker-Denoiser Architecture with Twin Networks for Monaural Sound Source Separation. - Konstantinos Drossos; Stylianos Ioannis Mimilakis; Dmitriy Serdyuk; Gerald Schuller; Tuomas Virtanen; Yoshua Bengio (IJCNN, 2018)

Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition. - Titouan Parcollet; Ying Zhang 033; Mohamed Morchid; Chiheb Trabelsi; Georges Linarès; Renato de Mori; Yoshua Bengio (INTERSPEECH, 2018)

Twin Regularization for Online Speech Recognition. - Mirco Ravanelli; Dmitriy Serdyuk; Yoshua Bengio (INTERSPEECH, 2018)

Image-to-image translation for cross-domain disentanglement. - Abel Gonzalez-Garcia; Joost van de Weijer 001; Yoshua Bengio (NeurIPS, 2018)

Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. - Nan Rosemary Ke; Anirudh Goyal; Olexa Bilaniuk; Jonathan Binas; Michael C. Mozer; Chris Pal; Yoshua Bengio (NeurIPS, 2018)

Dendritic cortical microcircuits approximate the backpropagation algorithm. - João Sacramento; Rui Ponte Costa; Yoshua Bengio; Walter Senn (NeurIPS, 2018)

Bayesian Model-Agnostic Meta-Learning. - Jaesik Yoon; Taesup Kim; Ousmane Dia; Sungwoong Kim; Yoshua Bengio; Sungjin Ahn (NeurIPS, 2018)

MetaGAN: An Adversarial Approach to Few-Shot Learning. - Ruixiang Zhang; Tong Che; Zoubin Ghahramani; Yoshua Bengio; Yangqiu Song (NeurIPS, 2018)

Learning Hierarchical Structures On-The-Fly with a Recurrent-Recursive Model for Sequences. - Athul Paul Jacob; Zhouhan Lin; Alessandro Sordoni; Yoshua Bengio (Rep4NLP@ACL, 2018)

Speaker Recognition from Raw Waveform with SincNet. - Mirco Ravanelli; Yoshua Bengio (SLT, 2018)

Deep convolutional networks for quality assessment of protein folds. - Georgy Derevyanko; Sergei Grudinin; Yoshua Bengio; Guillaume Lamoureux (Bioinform., 2018)

Dendritic error backpropagation in deep cortical microcircuits. - João Sacramento; Rui Ponte Costa; Yoshua Bengio; Walter Senn (CoRR, 2018)

ObamaNet: Photo-realistic lip-sync from text. - Rithesh Kumar; Jose Sotelo; Kundan Kumar; Alexandre de Brébisson; Yoshua Bengio (CoRR, 2018)

A3T: Adversarially Augmented Adversarial Training. - Akram Erraqabi; Aristide Baratin; Yoshua Bengio; Simon Lacoste-Julien (CoRR, 2018)

A Deep Reinforcement Learning Chatbot (Short Version). - Iulian Vlad Serban; Chinnadhurai Sankar; Mathieu Germain; Saizheng Zhang; Zhouhan Lin; Sandeep Subramanian; Taesup Kim; Michael Pieper; Sarath Chandar; Nan Rosemary Ke; Sai Rajeswar; Alexandre de Brébisson; et al. (CoRR, 2018)

Generalization in Machine Learning via Analytical Learning Theory. - Kenji Kawaguchi; Yoshua Bengio (CoRR, 2018)

A Walk with SGD. - Chen Xing; Devansh Arpit; Christos Tsirigotis; Yoshua Bengio (CoRR, 2018)

Learning Anonymized Representations with Adversarial Neural Networks. - Clément Feutry; Pablo Piantanida; Yoshua Bengio; Pierre Duhamel (CoRR, 2018)

Disentangling the independently controllable factors of variation by interacting with the world. - Valentin Thomas; Emmanuel Bengio; William Fedus; Jules Pondard; Philippe Beaudoin; Hugo Larochelle; Joelle Pineau; Doina Precup; Yoshua Bengio (CoRR, 2018)

Recall Traces: Backtracking Models for Efficient Reinforcement Learning. - Anirudh Goyal; Philemon Brakel; William Fedus; Timothy P. Lillicrap; Sergey Levine; Hugo Larochelle; Yoshua Bengio (CoRR, 2018)

Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations. - Alex Lamb; Jonathan Binas; Anirudh Goyal; Dmitriy Serdyuk; Sandeep Subramanian; Ioannis Mitliagkas; Yoshua Bengio (CoRR, 2018)

Commonsense mining as knowledge base completion? A study on the impact of novelty. - Stanislaw Jastrzebski; Dzmitry Bahdanau; Seyedarian Hosseini; Michael Noukhovitch; Yoshua Bengio; Jackie Chi Kit Cheung (CoRR, 2018)

Low-memory convolutional neural networks through incremental depth-first processing. - Jonathan Binas; Yoshua Bengio (CoRR, 2018)

Learning to rank for censored survival data. - Margaux Luck; Tristan Sylvain; Joseph Paul Cohen; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (CoRR, 2018)

Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. - Vikas Verma; Alex Lamb; Christopher Beckham; Aaron C. Courville; Ioannis Mitliagkas; Yoshua Bengio (CoRR, 2018)

Modularity Matters: Learning Invariant Relational Reasoning Tasks. - Jason Jo; Vikas Verma; Yoshua Bengio (CoRR, 2018)

Towards Gene Expression Convolutions using Gene Interaction Graphs. - Francis Dutil; Joseph Paul Cohen; Martin Weiss; Georgy Derevyanko; Yoshua Bengio (CoRR, 2018)

On the Spectral Bias of Deep Neural Networks. - Nasim Rahaman; Devansh Arpit; Aristide Baratin; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (CoRR, 2018)

DNN's Sharpest Directions Along the SGD Trajectory. - Stanislaw Jastrzebski; Zachary Kenton; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (CoRR, 2018)

Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning. - Eric Larsen; Sébastien Lachapelle; Yoshua Bengio; Emma Frejinger; Simon Lacoste-Julien; Andrea Lodi 001 (CoRR, 2018)

Generalization of Equilibrium Propagation to Vector Field Dynamics. - Benjamin Scellier; Anirudh Goyal; Jonathan Binas; Thomas Mesnard; Yoshua Bengio (CoRR, 2018)

Learning deep representations by mutual information estimation and maximization. - R. Devon Hjelm; Alex Fedorov; Samuel Lavoie-Marchildon; Karan Grewal; Adam Trischler; Yoshua Bengio (CoRR, 2018)

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding. - Nan Rosemary Ke; Anirudh Goyal; Olexa Bilaniuk; Jonathan Binas; Michael C. Mozer; Chris Pal; Yoshua Bengio (CoRR, 2018)

On the Learning Dynamics of Deep Neural Networks. - Remi Tachet des Combes; Mohammad Pezeshki; Samira Shabanian; Aaron C. Courville; Yoshua Bengio (CoRR, 2018)

Towards the Latent Transcriptome. - Assya Trofimov; Francis Dutil; Claude Perreault; Sébastien Lemieux; Yoshua Bengio; Joseph Paul Cohen (CoRR, 2018)

BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop. - Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Salem Lahlou; Lucas Willems; Chitwan Saharia; Thien Huu Nguyen; Yoshua Bengio (CoRR, 2018)

How can deep learning advance computational modeling of sensory information processing? - Jessica A. F. Thompson; Yoshua Bengio; Elia Formisano; Marc Schönwiesner (CoRR, 2018)

On Training Recurrent Neural Networks for Lifelong Learning. - Shagun Sodhani; Sarath Chandar; Yoshua Bengio (CoRR, 2018)

Interpretable Convolutional Filters with SincNet. - Mirco Ravanelli; Yoshua Bengio (CoRR, 2018)

DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation. - Rim Assouel; Mohamed Ahmed; Marwin H. S. Segler; Amir Saffari; Yoshua Bengio (CoRR, 2018)

Keep Drawing It: Iterative language-based image generation and editing. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (CoRR, 2018)

The effects of negative adaptation in Model-Agnostic Meta-Learning. - Tristan Deleu; Yoshua Bengio (CoRR, 2018)

Speech and Speaker Recognition from Raw Waveform with SincNet. - Mirco Ravanelli; Yoshua Bengio (CoRR, 2018)

Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks. - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (CoRR, 2018)

Fine-grained attention mechanism for neural machine translation. - Heeyoul Choi; Kyunghyun Cho; Yoshua Bengio (Neurocomputing, 2018)

Learning normalized inputs for iterative estimation in medical image segmentation. - Michal Drozdzal; Gabriel Chartrand; Eugene Vorontsov; Mahsa Shakeri; Lisa Di-Jorio; An Tang; Adriana Romero; Yoshua Bengio; Chris Pal; Samuel Kadoury (Medical Image Anal., 2018)

Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (Neural Comput., 2018)

Drawing and Recognizing Chinese Characters with Recurrent Neural Network. - Xu-Yao Zhang; Fei Yin; Yan-Ming Zhang 001; Cheng-Lin Liu 001; Yoshua Bengio (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Light Gated Recurrent Units for Speech Recognition. - Mirco Ravanelli; Philemon Brakel; Maurizio Omologo; Yoshua Bengio (IEEE Trans. Emerg. Top. Comput. Intell., 2018)

Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. - Sarath Chandar; Chinnadhurai Sankar; Eugene Vorontsov; Samira Ebrahimi Kahou; Yoshua Bengio (AAAI, 2019)

Combined Reinforcement Learning via Abstract Representations. - Vincent François-Lavet; Yoshua Bengio; Doina Precup; Joelle Pineau (AAAI, 2019)

Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. - Chinnadhurai Sankar; Sandeep Subramanian; Chris Pal; Sarath Chandar; Yoshua Bengio (ACL (1), 2019)

Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy. - Alex Lamb; Vikas Verma; Juho Kannala; Yoshua Bengio (AISec@CCS, 2019)

Interactive Language Learning by Question Answering. - Xingdi Yuan; Marc-Alexandre Côté; Jie Fu 001; Zhouhan Lin; Chris Pal; Yoshua Bengio; Adam Trischler (EMNLP/IJCNLP (1), 2019)

Representation Mixing for TTS Synthesis. - Kyle Kastner; João Felipe Santos; Yoshua Bengio; Aaron C. Courville (ICASSP, 2019)

The Pytorch-kaldi Speech Recognition Toolkit. - Mirco Ravanelli; Titouan Parcollet; Yoshua Bengio (ICASSP, 2019)

How Transferable Are Features in Convolutional Neural Network Acoustic Models across Languages? - Jessica A. F. Thompson; Marc Schönwiesner; Yoshua Bengio; Daniel Willett (ICASSP, 2019)

A Highly Adaptive Acoustic Model for Accurate Multi-dialect Speech Recognition. - Sanghyun Yoo; Inchul Song; Yoshua Bengio (ICASSP, 2019)

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (ICCV, 2019)

Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. - Md Mahfuzur Rahman Siddiquee; Zongwei Zhou; Nima Tajbakhsh; Ruibin Feng; Michael B. Gotway; Yoshua Bengio; Jianming Liang (ICCV, 2019)

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning. - Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Salem Lahlou; Lucas Willems; Chitwan Saharia; Thien Huu Nguyen; Yoshua Bengio (ICLR (Poster), 2019)

Adversarial Domain Adaptation for Stable Brain-Machine Interfaces. - Ali Farshchian; Juan Alvaro Gallego; Joseph Paul Cohen; Yoshua Bengio; Lee E. Miller; Sara A. Solla (ICLR (Poster), 2019)

Recall Traces: Backtracking Models for Efficient Reinforcement Learning. - Anirudh Goyal; Philemon Brakel; William Fedus; Soumye Singhal; Timothy P. Lillicrap; Sergey Levine; Hugo Larochelle; Yoshua Bengio (ICLR (Poster), 2019)

InfoBot: Transfer and Exploration via the Information Bottleneck. - Anirudh Goyal; Riashat Islam; Daniel Strouse; Zafarali Ahmed; Hugo Larochelle; Matthew M. Botvinick; Yoshua Bengio; Sergey Levine (ICLR (Poster), 2019)

Learning deep representations by mutual information estimation and maximization. - R. Devon Hjelm; Alex Fedorov; Samuel Lavoie-Marchildon; Karan Grewal; Philip Bachman; Adam Trischler; Yoshua Bengio (ICLR, 2019)

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. - Stanislaw Jastrzebski; Zachary Kenton; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICLR (Poster), 2019)

h-detach: Modifying the LSTM Gradient Towards Better Optimization. - Bhargav Kanuparthi; Devansh Arpit; Giancarlo Kerg; Nan Rosemary Ke; Ioannis Mitliagkas; Yoshua Bengio (ICLR (Poster), 2019)

Modeling the Long Term Future in Model-Based Reinforcement Learning. - Nan Rosemary Ke; Amanpreet Singh; Ahmed Touati; Anirudh Goyal; Yoshua Bengio; Devi Parikh; Dhruv Batra (ICLR (Poster), 2019)

Quaternion Recurrent Neural Networks. - Titouan Parcollet; Mirco Ravanelli; Mohamed Morchid; Georges Linarès; Chiheb Trabelsi; Renato De Mori; Yoshua Bengio (ICLR (Poster), 2019)

Probabilistic Planning with Sequential Monte Carlo methods. - Alexandre Piché; Valentin Thomas; Cyril Ibrahim; Yoshua Bengio; Chris Pal (ICLR (Poster), 2019)

An Empirical Study of Example Forgetting during Deep Neural Network Learning. - Mariya Toneva; Alessandro Sordoni; Remi Tachet des Combes; Adam Trischler; Yoshua Bengio; Geoffrey J. Gordon (ICLR (Poster), 2019)

Deep Graph Infomax. - Petar Velickovic; William Fedus; William L. Hamilton; Pietro Liò; Yoshua Bengio; R. Devon Hjelm (ICLR (Poster), 2019)

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. - Alex Lamb; Jonathan Binas; Anirudh Goyal; Sandeep Subramanian; Ioannis Mitliagkas; Yoshua Bengio; Michael Mozer (ICML, 2019)

GMNN: Graph Markov Neural Networks. - Meng Qu; Yoshua Bengio; Jian Tang 005 (ICML, 2019)

On the Spectral Bias of Neural Networks. - Nasim Rahaman; Aristide Baratin; Devansh Arpit; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (ICML, 2019)

Manifold Mixup: Better Representations by Interpolating Hidden States. - Vikas Verma; Alex Lamb; Christopher Beckham; Amir Najafi 002; Ioannis Mitliagkas; David Lopez-Paz; Yoshua Bengio (ICML, 2019)

A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies. - Homanga Bharadhwaj; Zihan Wang; Yoshua Bengio; Liam Paull (ICRA, 2019)

Interpolation Consistency Training for Semi-supervised Learning. - Vikas Verma; Alex Lamb; Juho Kannala; Yoshua Bengio; David Lopez-Paz (IJCAI, 2019)

Speech Model Pre-Training for End-to-End Spoken Language Understanding. - Loren Lugosch; Mirco Ravanelli; Patrick Ignoto; Vikrant Singh Tomar; Yoshua Bengio (INTERSPEECH, 2019)

Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks. - Santiago Pascual; Mirco Ravanelli; Joan Serrà; Antonio Bonafonte; Yoshua Bengio (INTERSPEECH, 2019)

Learning Speaker Representations with Mutual Information. - Mirco Ravanelli; Yoshua Bengio (INTERSPEECH, 2019)

InfoMask: Masked Variational Latent Representation to Localize Chest Disease. - Saeid Asgari Taghanaki; Mohammad Havaei; Tess Berthier; Francis Dutil; Lisa Di-Jorio; Ghassan Hamarneh; Yoshua Bengio (MICCAI (6), 2019)

Gradient based sample selection for online continual learning. - Rahaf Aljundi; Min Lin; Baptiste Goujaud; Yoshua Bengio (NeurIPS, 2019)

Unsupervised State Representation Learning in Atari. - Ankesh Anand; Evan Racah; Sherjil Ozair; Yoshua Bengio; Marc-Alexandre Côté; R. Devon Hjelm (NeurIPS, 2019)

How to Initialize your Network? Robust Initialization for WeightNorm & ResNets. - Devansh Arpit; Víctor Campos 001; Yoshua Bengio (NeurIPS, 2019)

On Adversarial Mixup Resynthesis. - Christopher Beckham; Sina Honari; Vikas Verma; Alex Lamb; Farnoosh Ghadiri; R. Devon Hjelm; Yoshua Bengio; Chris Pal (NeurIPS, 2019)

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (NeurIPS, 2019)

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. - Giancarlo Kerg; Kyle Goyette; Maximilian Puelma Touzel; Gauthier Gidel; Eugene Vorontsov; Yoshua Bengio; Guillaume Lajoie (NeurIPS, 2019)

Variational Temporal Abstraction. - Taesup Kim; Sungjin Ahn; Yoshua Bengio (NeurIPS, 2019)

MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. - Kundan Kumar; Rithesh Kumar; Thibault de Boissiere; Lucas Gestin; Wei Zhen Teoh; Jose Sotelo; Alexandre de Brébisson; Yoshua Bengio; Aaron C. Courville (NeurIPS, 2019)

Wasserstein Dependency Measure for Representation Learning. - Sherjil Ozair; Corey Lynch; Yoshua Bengio; Aäron van den Oord; Sergey Levine; Pierre Sermanet (NeurIPS, 2019)

The Benefits of Over-parameterization at Initialization in Deep ReLU Networks. - Devansh Arpit; Yoshua Bengio (CoRR, 2019)

Maximum Entropy Generators for Energy-Based Models. - Rithesh Kumar; Anirudh Goyal; Aaron C. Courville; Yoshua Bengio (CoRR, 2019)

Hyperbolic Discounting and Learning over Multiple Horizons. - William Fedus; Carles Gelada; Yoshua Bengio; Marc G. Bellemare; Hugo Larochelle (CoRR, 2019)

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future. - Nan Rosemary Ke; Amanpreet Singh; Ahmed Touati; Anirudh Goyal; Yoshua Bengio; Devi Parikh; Dhruv Batra (CoRR, 2019)

Online continual learning with no task boundaries. - Rahaf Aljundi; Min Lin; Baptiste Goujaud; Yoshua Bengio (CoRR, 2019)

Towards Standardization of Data Licenses: The Montreal Data License. - Misha Benjamin; Paul Gagnon; Negar Rostamzadeh; Chris Pal; Yoshua Bengio; Alex Shee (CoRR, 2019)

Reinforced Imitation in Heterogeneous Action Space. - Konrad Zolna; Negar Rostamzadeh; Yoshua Bengio; Sungjin Ahn; Pedro O. Pinheiro (CoRR, 2019)

GradMask: Reduce Overfitting by Regularizing Saliency. - Becks Simpson; Francis Dutil; Yoshua Bengio; Joseph Paul Cohen (CoRR, 2019)

Compositional generalization in a deep seq2seq model by separating syntax and semantics. - Jake Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (CoRR, 2019)

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks. - Victor Schmidt; Alexandra Luccioni; S. Karthik Mukkavilli; Narmada Balasooriya; Kris Sankaran; Jennifer T. Chayes; Yoshua Bengio (CoRR, 2019)

The Journey is the Reward: Unsupervised Learning of Influential Trajectories. - Jonathan Binas; Sherjil Ozair; Yoshua Bengio (CoRR, 2019)

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. - Alex Lamb; Jonathan Binas; Anirudh Goyal; Sandeep Subramanian; Ioannis Mitliagkas; Denis Kazakov; Yoshua Bengio; Michael C. Mozer (CoRR, 2019)

Learning Powerful Policies by Using Consistent Dynamics Model. - Shagun Sodhani; Anirudh Goyal; Tristan Deleu; Yoshua Bengio; Sergey Levine; Jian Tang 005 (CoRR, 2019)

Conditional Computation for Continual Learning. - Min Lin; Jie Fu 001; Yoshua Bengio (CoRR, 2019)

Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy. - Alex Lamb; Vikas Verma; Juho Kannala; Yoshua Bengio (CoRR, 2019)

Information matrices and generalization. - Valentin Thomas; Fabian Pedregosa; Bart van Merriënboer; Pierre-Antoine Manzagol; Yoshua Bengio; Nicolas Le Roux (CoRR, 2019)

Learning the Arrow of Time. - Nasim Rahaman; Steffen Wolf 001; Anirudh Goyal; Roman Remme; Yoshua Bengio (CoRR, 2019)

Weakly-supervised Knowledge Graph Alignment with Adversarial Learning. - Meng Qu; Jian Tang 005; Yoshua Bengio (CoRR, 2019)

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures. - Jordan Hoffmann; Louis Maestrati; Yoshihide Sawada; Jian Tang 005; Jean Michel D. Sellier; Yoshua Bengio (CoRR, 2019)

Torchmeta: A Meta-Learning library for PyTorch. - Tristan Deleu; Tobias Würfl; Mandana Samiei; Joseph Paul Cohen; Yoshua Bengio (CoRR, 2019)

Avoidance Learning Using Observational Reinforcement Learning. - David Venuto; Léonard Boussioux; Junhao Wang; Rola Dali; Jhelum Chakravorty; Yoshua Bengio; Doina Precup (CoRR, 2019)

GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. - Vikas Verma; Meng Qu; Alex Lamb; Yoshua Bengio; Juho Kannala; Jian Tang 005 (CoRR, 2019)

Underwhelming Generalization Improvements From Controlling Feature Attribution. - Joseph D. Viviano; Becks Simpson; Francis Dutil; Yoshua Bengio; Joseph Paul Cohen (CoRR, 2019)

Learning Neural Causal Models from Unknown Interventions. - Nan Rosemary Ke; Olexa Bilaniuk; Anirudh Goyal; Stefan Bauer; Hugo Larochelle; Chris Pal; Yoshua Bengio (CoRR, 2019)

Predicting ice flow using machine learning. - Yimeng Min; S. Karthik Mukkavilli; Yoshua Bengio (CoRR, 2019)

Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery. - Shawn Tan; Guillaume Androz; Ahmad Chamseddine; Pierre Fecteau; Aaron C. Courville; Yoshua Bengio; Joseph Paul Cohen (CoRR, 2019)

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks. - Thomas Mesnard; Gaëtan Vignoud; João Sacramento; Walter Senn; Yoshua Bengio (CoRR, 2019)

Automated curriculum generation for Policy Gradients from Demonstrations. - Anirudh Srinivasan; Dzmitry Bahdanau; Maxime Chevalier-Boisvert; Yoshua Bengio (CoRR, 2019)

Applying Knowledge Transfer for Water Body Segmentation in Peru. - Jessenia Gonzalez; Debjani Bhowmick; Cesar Beltran; Kris Sankaran; Yoshua Bengio (CoRR, 2019)

The effect of task and training on intermediate representations in convolutional neural networks revealed with modified RV similarity analysis. - Jessica A. F. Thompson; Yoshua Bengio; Marc Schönwiesner (CoRR, 2019)

CLOSURE: Assessing Systematic Generalization of CLEVR Models. - Dzmitry Bahdanau; Harm de Vries; Timothy J. O'Donnell; Shikhar Murty; Philippe Beaudoin; Yoshua Bengio; Aaron C. Courville (CoRR, 2019)

On the Morality of Artificial Intelligence. - Alexandra Luccioni; Yoshua Bengio (CoRR, 2019)

Gated Orthogonal Recurrent Units: On Learning to Forget. - Li Jing 001; Çaglar Gülçehre; John Peurifoy; Yichen Shen 001; Max Tegmark; Marin Soljacic; Yoshua Bengio (Neural Comput., 2019)

Equivalence of Equilibrium Propagation and Recurrent Backpropagation. - Benjamin Scellier; Yoshua Bengio (Neural Comput., 2019)

Depth with nonlinearity creates no bad local minima in ResNets. - Kenji Kawaguchi; Yoshua Bengio (Neural Networks, 2019)

Combating False Negatives in Adversarial Imitation Learning (Student Abstract). - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (AAAI, 2020)

Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach. - Wenyu Du; Zhouhan Lin; Yikang Shen; Timothy J. O'Donnell; Yoshua Bengio; Yue Zhang 004 (ACL, 2020)

Compositional Generalization by Factorizing Alignment and Translation. - Jacob L. Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (ACL (student), 2020)

A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. - Iulian Vlad Serban; Varun Gupta; Ekaterina Kochmar; Dung Do Vu; Robert Belfer; Joelle Pineau; Aaron C. Courville; Laurent Charlin; Yoshua Bengio (AIED (2), 2020)

On the interplay between noise and curvature and its effect on optimization and generalization. - Valentin Thomas; Fabian Pedregosa; Bart van Merriënboer; Pierre-Antoine Manzagol; Yoshua Bengio; Nicolas Le Roux (AISTATS, 2020)

Systematicity in a Recurrent Neural Network by Factorizing Syntax and Semantics. - Jacob L. Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (CogSci, 2020)

A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs. - Yoshua Bengio; Emma Frejinger; Andrea Lodi 001; Rahul Patel; Sriram Sankaranarayanan 002 (CPAIOR, 2020)

Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. - Md Rifat Arefin; Vincent Michalski; Pierre-Luc St-Charles; Alfredo Kalaitzis; Sookyung Kim; Samira Ebrahimi Kahou; Yoshua Bengio (CVPR Workshops, 2020)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (ECCV (8), 2020)

Experience Grounds Language. - Yonatan Bisk; Ari Holtzman; Jesse Thomason; Jacob Andreas; Yoshua Bengio; Joyce Chai; Mirella Lapata; Angeliki Lazaridou; Jonathan May; Aleksandr Nisnevich; Nicolas Pinto; Joseph P. Turian (EMNLP (1), 2020)

Multi-Task Self-Supervised Learning for Robust Speech Recognition. - Mirco Ravanelli; Jianyuan Zhong; Santiago Pascual; Pawel Swietojanski; João Monteiro 002; Jan Trmal; Yoshua Bengio (ICASSP, 2020)

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. - Yoshua Bengio; Tristan Deleu; Nasim Rahaman; Nan Rosemary Ke; Sébastien Lachapelle; Olexa Bilaniuk; Anirudh Goyal; Christopher J. Pal (ICLR, 2020)

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. - Anirudh Goyal; Yoshua Bengio; Matthew M. Botvinick; Sergey Levine (ICLR, 2020)

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. - Anirudh Goyal; Shagun Sodhani; Jonathan Binas; Xue Bin Peng; Sergey Levine; Yoshua Bengio (ICLR, 2020)

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (ICLR, 2020)

Learning the Arrow of Time for Problems in Reinforcement Learning. - Nasim Rahaman; Steffen Wolf 001; Anirudh Goyal; Roman Remme; Yoshua Bengio (ICLR, 2020)

Revisiting Fundamentals of Experience Replay. - William Fedus; Prajit Ramachandran; Rishabh Agarwal; Yoshua Bengio; Hugo Larochelle; Mark Rowland 001; Will Dabney (ICML, 2020)

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Simon Blackburn; Karam M. J. Thomas; Connor W. Coley; Jian Tang 005; Sarath Chandar; Yoshua Bengio (ICML, 2020)

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. - Sarthak Mittal; Alex Lamb; Anirudh Goyal; Vikram Voleti; Murray Shanahan; Guillaume Lajoie; Michael Mozer; Yoshua Bengio (ICML, 2020)

Small-GAN: Speeding up GAN Training using Core-Sets. - Samarth Sinha; Han Zhang 010; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Augustus Odena (ICML, 2020)

Perceptual Generative Autoencoders. - Zijun Zhang; Ruixiang Zhang; Zongpeng Li; Yoshua Bengio; Liam Paull (ICML, 2020)

Attention Based Pruning for Shift Networks. - Ghouthi Boukli Hacene; Carlos Lassance; Vincent Gripon; Matthieu Courbariaux; Yoshua Bengio (ICPR, 2020)

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (NEWCAS, 2020)

Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling. - Tong Che; Ruixiang Zhang; Jascha Sohl-Dickstein; Hugo Larochelle; Liam Paull; Yuan Cao; Yoshua Bengio (NeurIPS, 2020)

Hybrid Models for Learning to Branch. - Prateek Gupta; Maxime Gasse; Elias B. Khalil; Pawan Kumar Mudigonda; Andrea Lodi 001; Yoshua Bengio (NeurIPS, 2020)

Untangling tradeoffs between recurrence and self-attention in artificial neural networks. - Giancarlo Kerg; Bhargav Kanuparthi; Anirudh Goyal; Kyle Goyette; Yoshua Bengio; Guillaume Lajoie (NeurIPS, 2020)

Joint Learning of Generative Translator and Classifier for Visually Similar Classes. - ByungIn Yoo; Tristan Sylvain; Yoshua Bengio; Junmo Kim 002 (IEEE Access, 2020)

Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition. - Assya Trofimov; Joseph Paul Cohen; Yoshua Bengio; Claude Perreault; Sébastien Lemieux (Bioinform., 2020)

Generative adversarial networks. - Ian J. Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron C. Courville; Yoshua Bengio (Commun. ACM, 2020)

Learning from Learning Machines: Optimisation, Rules, and Social Norms. - Travis LaCroix; Yoshua Bengio (CoRR, 2020)

Universal Successor Features for Transfer Reinforcement Learning. - Chen Ma; Dylan R. Ashley; Junfeng Wen; Yoshua Bengio (CoRR, 2020)

Using Simulated Data to Generate Images of Climate Change. - Gautier Cosne; Adrien Juraver; Mélisande Teng; Victor Schmidt; Vahe Vardanyan; Alexandra Luccioni; Yoshua Bengio (CoRR, 2020)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (CoRR, 2020)

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery. - Michel Deudon; Alfredo Kalaitzis; Israel Goytom; Md Rifat Arefin; Zhichao Lin; Kris Sankaran; Vincent Michalski; Samira Ebrahimi Kahou; Julien Cornebise; Yoshua Bengio (CoRR, 2020)

Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning. - Devansh Arpit; Huan Wang 014; Caiming Xiong; Richard Socher; Yoshua Bengio (CoRR, 2020)

On Catastrophic Interference in Atari 2600 Games. - William Fedus; Dibya Ghosh; John D. Martin; Marc G. Bellemare; Yoshua Bengio; Hugo Larochelle (CoRR, 2020)

Benchmarking Graph Neural Networks. - Vijay Prakash Dwivedi; Chaitanya K. Joshi; Thomas Laurent 001; Yoshua Bengio; Xavier Bresson (CoRR, 2020)

Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay. - Qicheng Lao; Xiang Jiang 001; Mohammad Havaei; Yoshua Bengio (CoRR, 2020)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

Equilibrium Propagation with Continual Weight Updates. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

COVI White Paper. - Hannah Alsdurf; Yoshua Bengio; Tristan Deleu; Prateek Gupta; Daphne Ippolito; Richard Janda; Max Jarvie; Tyler Kolody; Sekoul Krastev; Tegan Maharaj; Robert Obryk; Dan Pilat; et al. (CoRR, 2020)

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. - Joseph Paul Cohen; Lan Dao; Paul Morrison; Karsten Roth; Yoshua Bengio; Beiyi Shen; Almas Abbasi; Mahsa Hoshmand-Kochi; Marzyeh Ghassemi; Haifang Li; Tim Q. Duong (CoRR, 2020)

Training End-to-End Analog Neural Networks with Equilibrium Propagation. - Jack D. Kendall; Ross D. Pantone; Kalpana Manickavasagam; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. - Axel Laborieux; Maxence Ernoult; Benjamin Scellier; Yoshua Bengio; Julie Grollier; Damien Querlioz (CoRR, 2020)

Learning Causal Models Online. - Khurram Javed; Martha White; Yoshua Bengio (CoRR, 2020)

Untangling tradeoffs between recurrence and self-attention in neural networks. - Giancarlo Kerg; Bhargav Kanuparthi; Anirudh Goyal; Kyle Goyette; Yoshua Bengio; Guillaume Lajoie (CoRR, 2020)

HNHN: Hypergraph Networks with Hyperedge Neurons. - Yihe Dong; Will Sawin; Yoshua Bengio (CoRR, 2020)

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. - Matthew Amodio; Rim Assouel; Victor Schmidt; Tristan Sylvain; Smita Krishnaswamy; Yoshua Bengio (CoRR, 2020)

Rethinking Distributional Matching Based Domain Adaptation. - Bo Li 080; Yezhen Wang; Tong Che; Shanghang Zhang; Sicheng Zhao; Pengfei Xu 013; Wei Zhou; Yoshua Bengio; Kurt Keutzer (CoRR, 2020)

Hybrid Models for Learning to Branch. - Prateek Gupta; Maxime Gasse; Elias B. Khalil; M. Pawan Kumar; Andrea Lodi 001; Yoshua Bengio (CoRR, 2020)

Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Sergey Levine; Charles Blundell; Yoshua Bengio; Michael Mozer (CoRR, 2020)

S2RMs: Spatially Structured Recurrent Modules. - Nasim Rahaman; Anirudh Goyal; Muhammad Waleed Gondal; Manuel Wuthrich; Stefan Bauer; Yash Sharma 001; Yoshua Bengio; Bernhard Schölkopf (CoRR, 2020)

BabyAI 1.1. - David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (CoRR, 2020)

Deriving Differential Target Propagation from Iterating Approximate Inverses. - Yoshua Bengio (CoRR, 2020)

Mastering Rate based Curriculum Learning. - Lucas Willems; Salem Lahlou; Yoshua Bengio (CoRR, 2020)

Cross-Modal Information Maximization for Medical Imaging: CMIM. - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (CoRR, 2020)

NU-GAN: High resolution neural upsampling with GAN. - Rithesh Kumar; Kundan Kumar; Vicki Anand; Yoshua Bengio; Aaron C. Courville (CoRR, 2020)

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. - Prateek Gupta; Tegan Maharaj; Martin Weiss; Nasim Rahaman; Hannah Alsdurf; Abhinav Sharma; Nanor Minoyan; Soren Harnois-Leblanc; Victor Schmidt; Pierre-Luc St-Charles; Tristan Deleu; Andrew Williams; et al. (CoRR, 2020)

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design. - Cheng-Hao Liu; Maksym Korablyov; Stanislaw Jastrzebski; Pawel Wlodarczyk-Pruszynski; Yoshua Bengio; Marwin H. S. Segler (CoRR, 2020)

Inductive Biases for Deep Learning of Higher-Level Cognition. - Anirudh Goyal; Yoshua Bengio (CoRR, 2020)

Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya. - Shimaa Baraka; Benjamin Akera; Bibek Aryal; Tenzing Chogyal Sherpa; Finu Shresta; Anthony Ortiz; Kris Sankaran; Juan Lavista Ferres; Mir Matin; Yoshua Bengio (CoRR, 2020)

The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. - Iulian Vlad Serban; Chinnadhurai Sankar; Michael Pieper; Joelle Pineau; Yoshua Bengio (J. Artif. Intell. Res., 2020)

Establishing an evaluation metric to quantify climate change image realism. - Sharon Zhou; Alexandra Luccioni; Gautier Cosne; Michael S. Bernstein; Yoshua Bengio (Mach. Learn. Sci. Technol., 2020)

Toward Training Recurrent Neural Networks for Lifelong Learning. - Shagun Sodhani; Sarath Chandar; Yoshua Bengio (Neural Comput., 2020)

On the Morality of Artificial Intelligence [Commentary]. - Alexandra Luccioni; Yoshua Bengio (IEEE Technol. Soc. Mag., 2020)

Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models. - Tong Che; Xiaofeng Liu 001; Site Li; Yubin Ge; Ruixiang Zhang; Caiming Xiong; Yoshua Bengio (AAAI, 2021)

Visual Concept Reasoning Networks. - Taesup Kim; Sungwoong Kim; Yoshua Bengio (AAAI, 2021)

Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting. - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (AAAI, 2021)

Object-Centric Image Generation from Layouts. - Tristan Sylvain; Pengchuan Zhang; Yoshua Bengio; R. Devon Hjelm; Shikhar Sharma 001 (AAAI, 2021)

GraphMix: Improved Training of GNNs for Semi-Supervised Learning. - Vikas Verma; Meng Qu; Kenji Kawaguchi; Alex Lamb; Yoshua Bengio; Juho Kannala; Jian Tang 005 (AAAI, 2021)

Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies. - Giulia Zarpellon; Jason Jo; Andrea Lodi 001; Yoshua Bengio (AAAI, 2021)

A Comparative Study of Learning Outcomes for Online Learning Platforms. - François St-Hilaire; Nathan Burns; Robert Belfer; Muhammad Shayan; Ariella Smofsky; Dung Do Vu; Antoine Frau; Joseph Potochny; Farid Faraji; Vincent Pavero; Neroli Ko; Ansona Onyi Ching; et al. (AIED (2), 2021)

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. - Alex Lamb; Anirudh Goyal; Agnieszka Slowik; Michael Mozer; Philippe Beaudoin; Yoshua Bengio (AISTATS, 2021)

An Analysis of the Adaptation Speed of Causal Models. - Rémi Le Priol; Reza Babanezhad 001; Yoshua Bengio; Simon Lacoste-Julien (AISTATS, 2021)

CMIM: Cross-Modal Information Maximization For Medical Imaging. - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (ICASSP, 2021)

FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters. - Yuwei Cheng; Jiannan Zhu; Mengxin Jiang; Jie Fu 001; Changsong Pang; Peidong Wang; Kris Sankaran; Olawale Onabola; Yimin Liu; Dianbo Liu; Yoshua Bengio (ICCV, 2021)

Systematic generalisation with group invariant predictions. - Faruk Ahmed; Yoshua Bengio; Harm van Seijen; Aaron C. Courville (ICLR, 2021)

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. - Ossama Ahmed; Frederik Träuble; Anirudh Goyal; Alexander Neitz; Manuel Wuthrich; Yoshua Bengio; Bernhard Schölkopf; Stefan Bauer (ICLR, 2021)

Predicting Infectiousness for Proactive Contact Tracing. - Yoshua Bengio; Prateek Gupta; Tegan Maharaj; Nasim Rahaman; Martin Weiss; Tristan Deleu; Eilif Benjamin Müller; Meng Qu; Victor Schmidt; Pierre-Luc St-Charles; Hannah Alsdurf; Olexa Bilaniuk; et al. (ICLR, 2021)

Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Charles Blundell; Sergey Levine; Yoshua Bengio; Michael Curtis Mozer (ICLR, 2021)

Recurrent Independent Mechanisms. - Anirudh Goyal; Alex Lamb; Jordan Hoffmann; Shagun Sodhani; Sergey Levine; Yoshua Bengio; Bernhard Schölkopf (ICLR, 2021)

Fast And Slow Learning Of Recurrent Independent Mechanisms. - Kanika Madan; Nan Rosemary Ke; Anirudh Goyal; Bernhard Schölkopf; Yoshua Bengio (ICLR, 2021)

RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. - Meng Qu; Jun-Kun Chen; Louis-Pascal A. C. Xhonneux; Yoshua Bengio; Jian Tang 005 (ICLR, 2021)

Spatially Structured Recurrent Modules. - Nasim Rahaman; Anirudh Goyal; Muhammad Waleed Gondal; Manuel Wuthrich; Stefan Bauer; Yash Sharma 001; Yoshua Bengio; Bernhard Schölkopf (ICLR, 2021)

Saliency is a Possible Red Herring When Diagnosing Poor Generalization. - Joseph D. Viviano; Becks Simpson; Francis Dutil; Yoshua Bengio; Joseph Paul Cohen (ICLR, 2021)

Learning Neural Generative Dynamics for Molecular Conformation Generation. - Minkai Xu; Shitong Luo; Yoshua Bengio; Jian Peng 001; Jian Tang 005 (ICLR, 2021)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. - Minkai Xu; Wujie Wang; Shitong Luo; Chence Shi; Yoshua Bengio; Rafael Gómez-Bombarelli; Jian Tang 005 (ICML, 2021)

Combating False Negatives in Adversarial Imitation Learning. - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (IJCNN, 2021)

hBERT + BiasCorp - Fighting Racism on the Web. - Olawale Onabola; Zhuang Ma; Yang Xie; Benjamin Akera; Abdulrahman Ibraheem; Jia Xue; Dianbo Liu; Yoshua Bengio (LT-EDI@EACL, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Jean-Christophe Gagnon-Audet; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (NeurIPS, 2021)

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. - Emmanuel Bengio; Moksh Jain; Maksym Korablyov; Doina Precup; Yoshua Bengio (NeurIPS, 2021)

Neural Production Systems. - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Charles Blundell; Philippe Beaudoin; Nicolas Heess; Michael Mozer; Yoshua Bengio (NeurIPS, 2021)

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. - Nan Rosemary Ke; Aniket Didolkar; Sarthak Mittal; Anirudh Goyal; Guillaume Lajoie; Stefan Bauer; Danilo Jimenez Rezende; Michael Mozer; Yoshua Bengio; Chris Pal (NeurIPS Datasets and Benchmarks, 2021)

Discrete-Valued Neural Communication. - Dianbo Liu; Alex Lamb; Kenji Kawaguchi; Anirudh Goyal; Chen Sun 007; Michael C. Mozer; Yoshua Bengio (NeurIPS, 2021)

Gradient Starvation: A Learning Proclivity in Neural Networks. - Mohammad Pezeshki; Sékou-Oumar Kaba; Yoshua Bengio; Aaron C. Courville; Doina Precup; Guillaume Lajoie (NeurIPS, 2021)

Dynamic Inference with Neural Interpreters. - Nasim Rahaman; Muhammad Waleed Gondal; Shruti Joshi; Peter V. Gehler; Yoshua Bengio; Francesco Locatello; Bernhard Schölkopf (NeurIPS, 2021)

The Causal-Neural Connection: Expressiveness, Learnability, and Inference. - Kevin Xia 001; Kai-Zhan Lee; Yoshua Bengio; Elias Bareinboim (NeurIPS, 2021)

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. - Mingde Zhao 001; Zhen Liu 019; Sitao Luan; Shuyuan Zhang; Doina Precup; Yoshua Bengio (NeurIPS, 2021)

Exploring the Wasserstein metric for time-to-event analysis. - Tristan Sylvain; Margaux Luck; Joseph Paul Cohen; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (SPACA, 2021)

Deep learning for AI. - Yoshua Bengio; Yann LeCun; Geoffrey E. Hinton (Commun. ACM, 2021)

Using Artificial Intelligence to Visualize the Impacts of Climate Change. - Alexandra Luccioni; Victor Schmidt; Vahe Vardanyan; Yoshua Bengio; Theresa-Marie Rhyne (IEEE Computer Graphics and Applications, 2021)

Structured Sparsity Inducing Adaptive Optimizers for Deep Learning. - Tristan Deleu; Yoshua Bengio (CoRR, 2021)

Towards Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (CoRR, 2021)

Transformers with Competitive Ensembles of Independent Mechanisms. - Alex Lamb; Di He 001; Anirudh Goyal; Guolin Ke; Chien-Feng Liao; Mirco Ravanelli; Yoshua Bengio (CoRR, 2021)

SpeechBrain: A General-Purpose Speech Toolkit. - Mirco Ravanelli; Titouan Parcollet; Peter Plantinga; Aku Rouhe; Samuele Cornell; Loren Lugosch; Cem Subakan; Nauman Dawalatabad; Abdelwahab Heba; Jianyuan Zhong; Ju-Chieh Chou; Sung-Lin Yeh; et al. (CoRR, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (CoRR, 2021)

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. - Yashas Annadani; Jonas Rothfuss; Alexandre Lacoste; Nino Scherrer; Anirudh Goyal; Yoshua Bengio; Stefan Bauer (CoRR, 2021)

Predicting Unreliable Predictions by Shattering a Neural Network. - Xu Ji; Razvan Pascanu; R. Devon Hjelm; Andrea Vedaldi; Balaji Lakshminarayanan; Yoshua Bengio (CoRR, 2021)

Learning Neural Causal Models with Active Interventions. - Nino Scherrer; Olexa Bilaniuk; Yashas Annadani; Anirudh Goyal; Patrick Schwab; Bernhard Schölkopf; Michael C. Mozer; Yoshua Bengio; Stefan Bauer; Nan Rosemary Ke (CoRR, 2021)

Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond. - Dinghuai Zhang; Jie Fu 001; Yoshua Bengio; Aaron C. Courville (CoRR, 2021)

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. - Nicholas Roy; Ingmar Posner; Tim D. Barfoot; Philippe Beaudoin; Yoshua Bengio; Jeannette Bohg; Oliver Brock; Isabelle Depatie; Dieter Fox; Daniel E. Koditschek; Tomás Lozano-Pérez; Vikash Mansinghka 001; et al. (CoRR, 2021)

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models. - Enoch Tetteh; Joseph D. Viviano; Yoshua Bengio; David Krueger 001; Joseph Paul Cohen (CoRR, 2021)

Machine learning for combinatorial optimization: A methodological tour d'horizon. - Yoshua Bengio; Andrea Lodi 001; Antoine Prouvost (Eur. J. Oper. Res., 2021)

Inherent privacy limitations of decentralized contact tracing apps. - Yoshua Bengio; Daphne Ippolito; Richard Janda; Max Jarvie; Benjamin Prud'homme; Jean-Franois Rousseau; Abhinav Sharma; Yun William Yu (J. Am. Medical Informatics Assoc., 2021)

Toward Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (Proc. IEEE, 2021)

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation. - Tariq Daouda; Maude Dumont-Lagacé; Albert Feghaly; Yahya Benslimane; Rébecca Panes; Mathieu Courcelles; Mohamed Benhammadi; Lea Harrington; Pierre Thibault; François Major; Yoshua Bengio; Etienne Gagnon; et al. (PLoS Comput. Biol., 2021)

PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. - Tianyi Zhang; Shirui Zhang; Ziwei Chen; Yoshua Bengio; Dianbo Liu (IEEE Big Data, 2022)

VIM: Variational Independent Modules for Video Prediction. - Rim Assouel; Lluís Castrejón; Aaron C. Courville; Nicolas Ballas; Yoshua Bengio (CLeaR, 2022)

Properties from mechanisms: an equivariance perspective on identifiable representation learning. - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (ICLR, 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation. - Tristan Deleu; David Kanaa; Leo Feng; Giancarlo Kerg; Yoshua Bengio; Guillaume Lajoie; Pierre-Luc Bacon (ICLR, 2022)

Graph Neural Networks with Learnable Structural and Positional Representations. - Vijay Prakash Dwivedi; Anh Tuan Luu; Thomas Laurent 001; Yoshua Bengio; Xavier Bresson (ICLR, 2022)

Coordination Among Neural Modules Through a Shared Global Workspace. - Anirudh Goyal; Aniket Rajiv Didolkar; Alex Lamb; Kartikeya Badola; Nan Rosemary Ke; Nasim Rahaman; Jonathan Binas; Charles Blundell; Michael Curtis Mozer; Yoshua Bengio (ICLR, 2022)

Compositional Attention: Disentangling Search and Retrieval. - Sarthak Mittal; Sharath Chandra Raparthy; Irina Rish; Yoshua Bengio; Guillaume Lajoie (ICLR, 2022)

Chunked Autoregressive GAN for Conditional Waveform Synthesis. - Max Morrison; Rithesh Kumar; Kundan Kumar; Prem Seetharaman; Aaron C. Courville; Yoshua Bengio (ICLR, 2022)

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. - Victor Schmidt; Alexandra Luccioni; Mélisande Teng; Tianyu Zhang; Alexia Reynaud; Sunand Raghupathi; Gautier Cosne; Adrien Juraver; Vahe Vardanyan; Alex Hernández-García; Yoshua Bengio (ICLR, 2022)

Unifying Likelihood-free Inference with Black-box Optimization and Beyond. - Dinghuai Zhang; Jie Fu 001; Yoshua Bengio; Aaron C. Courville (ICLR, 2022)

Towards Scaling Difference Target Propagation by Learning Backprop Targets. - Maxence Ernoult; Fabrice Normandin; Abhinav Moudgil; Sean Spinney; Eugene Belilovsky; Irina Rish; Blake A. Richards; Yoshua Bengio (ICML, 2022)

Biological Sequence Design with GFlowNets. - Moksh Jain; Emmanuel Bengio; Alex Hernández-García; Jarrid Rector-Brooks; Bonaventure F. P. Dossou; Chanakya Ajit Ekbote; Jie Fu 001; Tianyu Zhang; Michael Kilgour; Dinghuai Zhang; Lena Simine; Payel Das; et al. (ICML, 2022)

Multi-scale Feature Learning Dynamics: Insights for Double Descent. - Mohammad Pezeshki; Amartya Mitra; Yoshua Bengio; Guillaume Lajoie (ICML, 2022)

Generative Flow Networks for Discrete Probabilistic Modeling. - Dinghuai Zhang; Nikolay Malkin; Zhen Liu 019; Alexandra Volokhova; Aaron C. Courville; Yoshua Bengio (ICML, 2022)

Building Robust Ensembles via Margin Boosting. - Dinghuai Zhang; Hongyang Zhang 001; Aaron C. Courville; Yoshua Bengio; Pradeep Ravikumar; Arun Sai Suggala (ICML, 2022)

Weakly Supervised Representation Learning with Sparse Perturbations. - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (NeurIPS, 2022)

MAgNet: Mesh Agnostic Neural PDE Solver. - Oussama Boussif; Yoshua Bengio; Loubna Benabbou; Dan Assouline (NeurIPS, 2022)

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. - Aniket Didolkar; Kshitij Gupta; Anirudh Goyal; Nitesh B. Gundavarapu; Alex Lamb; Nan Rosemary Ke; Yoshua Bengio (NeurIPS, 2022)

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. - Jose Gallego-Posada; Juan Ramirez; Akram Erraqabi; Yoshua Bengio; Simon Lacoste-Julien (NeurIPS, 2022)

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (NeurIPS, 2022)

Trajectory balance: Improved credit assignment in GFlowNets. - Nikolay Malkin; Moksh Jain; Emmanuel Bengio; Chen Sun 007; Yoshua Bengio (NeurIPS, 2022)

Is a Modular Architecture Enough? - Sarthak Mittal; Yoshua Bengio; Guillaume Lajoie (NeurIPS, 2022)

Neural Attentive Circuits. - Martin Weiss; Nasim Rahaman; Francesco Locatello; Chris Pal; Yoshua Bengio; Bernhard Schölkopf; Li Erran Li; Nicolas Ballas (NeurIPS, 2022)

Bayesian structure learning with generative flow networks. - Tristan Deleu; António Góis; Chris Emezue; Mansi Rankawat; Simon Lacoste-Julien; Stefan Bauer; Yoshua Bengio (UAI, 2022)

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. - Akram Erraqabi; Marlos C. Machado; Mingde Zhao 001; Sainbayar Sukhbaatar; Alessandro Lazaric; Ludovic Denoyer; Yoshua Bengio (UAI, 2022)

Rethinking Learning Dynamics in RL using Adversarial Networks. - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (CoRR, 2022)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Notsawo; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (CoRR, 2022)

RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro. - Paul Bertin; Jarrid Rector-Brooks; Deepak Sharma; Thomas Gaudelet; Andrew Anighoro; Torsten Gross; Francisco Martinez-Pena; Eileen L. Tang; Suraj M. S; Cristian Regep; Jeremy B. R. Hayter; Maksym Korablyov; et al. (CoRR, 2022)

A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions. - François St-Hilaire; Dung Do Vu; Antoine Frau; Nathan Burns; Farid Faraji; Joseph Potochny; Stephane Robert; Arnaud Roussel; Selene Zheng; Taylor Glazier; Junfel Vincent Romano; Robert Belfer; et al. (CoRR, 2022)

(Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment. - Yoshua Bengio; Prateek Gupta; Dylan R. Radovic; Maarten Scholl; Andrew Williams; Christian Schröder de Witt; Tianyu Zhang; Yang Zhang (CoRR, 2022)

FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data. - Mike He Zhu; Léna Néhale Ezzine; Dianbo Liu; Yoshua Bengio (CoRR, 2022)

Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. - Dianbo Liu; Vedant Shah; Oussama Boussif; Cristian Meo; Anirudh Goyal; Tianmin Shu; Michael Mozer; Nicolas Heess; Yoshua Bengio (CoRR, 2022)

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. - Aniket Didolkar; Kshitij Gupta; Anirudh Goyal; Alex Lamb; Nan Rosemary Ke; Yoshua Bengio (CoRR, 2022)

Agnostic Physics-Driven Deep Learning. - Benjamin Scellier; Siddhartha Mishra; Yoshua Bengio; Yann Ollivier (CoRR, 2022)

On the Generalization and Adaption Performance of Causal Models. - Nino Scherrer; Anirudh Goyal; Stefan Bauer; Yoshua Bengio; Nan Rosemary Ke (CoRR, 2022)

On Neural Architecture Inductive Biases for Relational Tasks. - Giancarlo Kerg; Sarthak Mittal; David Rolnick; Yoshua Bengio; Blake A. Richards; Guillaume Lajoie (CoRR, 2022)

Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One. - Yezhen Wang; Tong Che; Bo Li 080; Kaitao Song; Hengzhi Pei; Yoshua Bengio; Dongsheng Li 002 (CoRR, 2022)

Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning. - Siba Moussa; Michael Kilgour; Clara Jans; Alex Hernández-García; Miroslava Cuperlovic-Culf; Yoshua Bengio; Lena Simine (CoRR, 2022)

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. - Tianyu Zhang; Andrew Williams; Soham Phade; Sunil Srinivasa; Yang Zhang; Prateek Gupta; Yoshua Bengio; Stephan Zheng (CoRR, 2022)

Unifying Generative Models with GFlowNets. - Dinghuai Zhang; Ricky T. Q. Chen; Nikolay Malkin; Yoshua Bengio (CoRR, 2022)

Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization. - Leo Feng; Padideh Nouri; Aneri Muni; Yoshua Bengio; Pierre-Luc Bacon (CoRR, 2022)

Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. - Bonaventure F. P. Dossou; Dianbo Liu; Xu Ji; Moksh Jain; Almer M. van der Sloot; Roger Palou; Michael Tyers; Yoshua Bengio (CoRR, 2022)

Contrastive introspection (ConSpec) to rapidly identify invariant steps for success. - Chen Sun 007; Wannan Yang; Benjamin Alsbury-Nealy; Yoshua Bengio; Blake A. Richards (CoRR, 2022)

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. - Anthony Zador; Blake A. Richards; Bence Ölveczky; Sean Escola; Yoshua Bengio; Kwabena Boahen 001; Matthew M. Botvinick; Dmitri B. Chklovskii; Anne Churchland; Claudia Clopath; James DiCarlo; Surya Ganguli; et al. (CoRR, 2022)

FL Games: A Federated Learning Framework for Distribution Shifts. - Sharut Gupta; Kartik Ahuja; Mohammad Havaei; Niladri Chatterjee; Yoshua Bengio (CoRR, 2022)

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (CoRR, 2022)

Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. - Chanakya Ekbote; Moksh Jain; Payel Das; Yoshua Bengio (CoRR, 2022)

A General Purpose Neural Architecture for Geospatial Systems. - Nasim Rahaman; Martin Weiss; Frederik Träuble; Francesco Locatello; Alexandre Lacoste; Yoshua Bengio; Chris Pal; Li Erran Li; Bernhard Schölkopf (CoRR, 2022)

Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes. - Mizu Nishikawa-Toomey; Tristan Deleu; Jithendaraa Subramanian; Yoshua Bengio; Laurent Charlin (CoRR, 2022)

Posterior samples of source galaxies in strong gravitational lenses with score-based priors. - Alexandre Adam; Adam Coogan; Nikolay Malkin; Ronan Legin; Laurence Perreault Levasseur; Yashar Hezaveh; Yoshua Bengio (CoRR, 2022)

Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (CoRR, 2022)

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. - Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham 001; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (CoRR, 2022)

Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. - Eric Larsen; Sébastien Lachapelle; Yoshua Bengio; Emma Frejinger; Simon Lacoste-Julien; Andrea Lodi 001 (INFORMS J. Comput., 2022)

RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. - Cheng-Hao Liu; Maksym Korablyov; Stanislaw Jastrzebski; Pawel Wlodarczyk-Pruszynski; Yoshua Bengio; Marwin H. S. Segler (J. Chem. Inf. Model., 2022)

Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. - Alex Lamb; Vikas Verma; Kenji Kawaguchi; Alexander Matyasko; Savya Khosla; Juho Kannala; Yoshua Bengio (Neural Networks, 2022)

Interpolation consistency training for semi-supervised learning. - Vikas Verma; Kenji Kawaguchi; Alex Lamb; Juho Kannala; Arno Solin; Yoshua Bengio; David Lopez-Paz (Neural Networks, 2022)

Lookback for Learning to Branch. - Prateek Gupta; Elias Boutros Khalil; Didier Chételat; Maxime Gasse; Andrea Lodi 001; Yoshua Bengio; M. Pawan Kumar (Trans. Mach. Learn. Res., 2022)

A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay. - Qicheng Lao; Xiang Jiang 001; Mohammad Havaei; Yoshua Bengio (IEEE Trans. Neural Networks Learn. Syst., 2022)

The Effect of Diversity in Meta-Learning. - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (AAAI, 2023)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Tikeng Notsawo Jr.; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (AAAI, 2023)

Combining Parameter-efficient Modules for Task-level Generalisation. - Edoardo Maria Ponti; Alessandro Sordoni; Yoshua Bengio; Siva Reddy (EACL, 2023)

Latent Bottlenecked Attentive Neural Processes. - Leo Feng; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (ICLR, 2023)

Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. - Dianbo Liu; Vedant Shah; Oussama Boussif; Cristian Meo; Anirudh Goyal; Tianmin Shu; Michael Curtis Mozer; Nicolas Heess; Yoshua Bengio (ICLR, 2023)

GFlowNets and variational inference. - Nikolay Malkin; Salem Lahlou; Tristan Deleu; Xu Ji; Edward J. Hu; Katie Everett; Dinghuai Zhang; Yoshua Bengio (ICLR, 2023)

Generative Augmented Flow Networks. - Ling Pan; Dinghuai Zhang; Aaron C. Courville; Longbo Huang; Yoshua Bengio (ICLR, 2023)

Predictive Inference with Feature Conformal Prediction. - Jiaye Teng; Chuan Wen; Dinghuai Zhang; Yoshua Bengio; Yang Gao 029; Yang Yuan (ICLR, 2023)

Latent State Marginalization as a Low-cost Approach for Improving Exploration. - Dinghuai Zhang; Aaron C. Courville; Yoshua Bengio; Qinqing Zheng; Amy Zhang 001; Ricky T. Q. Chen (ICLR, 2023)

Robust and Controllable Object-Centric Learning through Energy-based Models. - Ruixiang Zhang; Tong Che; Boris Ivanovic; Renhao Wang; Marco Pavone 001; Yoshua Bengio; Liam Paull (ICLR, 2023)

Interventional Causal Representation Learning. - Kartik Ahuja; Divyat Mahajan; Yixin Wang; Yoshua Bengio (ICML, 2023)

FAENet: Frame Averaging Equivariant GNN for Materials Modeling. - Alexandre Duval; Victor Schmidt; Alex Hernández-García; Santiago Miret; Fragkiskos D. Malliaros; Yoshua Bengio; David Rolnick (ICML, 2023)

GFlowNet-EM for Learning Compositional Latent Variable Models. - Edward J. Hu; Nikolay Malkin; Moksh Jain; Katie E. Everett; Alexandros Graikos; Yoshua Bengio (ICML, 2023)

Multi-Objective GFlowNets. - Moksh Jain; Sharath Chandra Raparthy; Alex Hernández-García; Jarrid Rector-Brooks; Yoshua Bengio; Santiago Miret; Emmanuel Bengio (ICML, 2023)

Equivariance with Learned Canonicalization Functions. - Sékou-Oumar Kaba; Arnab Kumar Mondal; Yan Zhang 067; Yoshua Bengio; Siamak Ravanbakhsh (ICML, 2023)

Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (ICML, 2023)

A theory of continuous generative flow networks. - Salem Lahlou; Tristan Deleu; Pablo Lemos; Dinghuai Zhang; Alexandra Volokhova; Alex Hernández-García; Léna Néhale Ezzine; Yoshua Bengio; Nikolay Malkin (ICML, 2023)

GFlowOut: Dropout with Generative Flow Networks. - Dianbo Liu; Moksh Jain; Bonaventure F. P. Dossou; Qianli Shen; Salem Lahlou; Anirudh Goyal; Nikolay Malkin; Chris Chinenye Emezue; Dinghuai Zhang; Nadhir Hassen; Xu Ji; Kenji Kawaguchi; et al. (ICML, 2023)

Learning GFlowNets From Partial Episodes For Improved Convergence And Stability. - Kanika Madan; Jarrid Rector-Brooks; Maksym Korablyov; Emmanuel Bengio; Moksh Jain; Andrei Cristian Nica; Tom Bosc; Yoshua Bengio; Nikolay Malkin (ICML, 2023)

Better Training of GFlowNets with Local Credit and Incomplete Trajectories. - Ling Pan; Nikolay Malkin; Dinghuai Zhang; Yoshua Bengio (ICML, 2023)

Hyena Hierarchy: Towards Larger Convolutional Language Models. - Michael Poli; Stefano Massaroli; Eric Nguyen; Daniel Y. Fu; Tri Dao; Stephen Baccus; Yoshua Bengio; Stefano Ermon; Christopher Ré (ICML, 2023)

Discrete Key-Value Bottleneck. - Frederik Träuble; Anirudh Goyal; Nasim Rahaman; Michael Curtis Mozer; Kenji Kawaguchi; Yoshua Bengio; Bernhard Schölkopf (ICML, 2023)

Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL. - Chen Sun 007; Wannan Yang; Thomas Jiralerspong; Dane Malenfant; Benjamin Alsbury-Nealy; Yoshua Bengio; Blake A. Richards (NeurIPS, 2023)

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets. - Lazar Atanackovic; Alexander Tong 001; Bo Wang; Leo J. Lee; Yoshua Bengio; Jason S. Hartford (NeurIPS, 2023)

Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context. - Oussama Boussif; Ghait Boukachab; Dan Assouline; Stefano Massaroli; Tianle Yuan; Loubna Benabbou; Yoshua Bengio (NeurIPS, 2023)

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. - Tristan Deleu; Mizu Nishikawa-Toomey; Jithendaraa Subramanian; Nikolay Malkin; Laurent Charlin; Yoshua Bengio (NeurIPS, 2023)

GEO-Bench: Toward Foundation Models for Earth Monitoring. - Alexandre Lacoste; Nils Lehmann; Pau Rodríguez; Evan D. Sherwin; Hannah Kerner; Björn Lütjens; Jeremy Irvin; David Dao; Hamed Alemohammad; Alexandre Drouin; Mehmet Gunturkun; Gabriel Huang; et al. (NeurIPS, 2023)

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. - Stefano Massaroli; Michael Poli; Daniel Y. Fu; Hermann Kumbong; Rom N. Parnichkun; David W. Romero; Aman Timalsina; Quinn McIntyre; Beidi Chen; Atri Rudra; Ce Zhang 001; Christopher Ré; et al. (NeurIPS, 2023)

Reusable Slotwise Mechanisms. - Bailey Trang Nguyen; Amin Mansouri; Kanika Madan; Khuong Nguyen; Kartik Ahuja; Dianbo Liu; Yoshua Bengio (NeurIPS, 2023)

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. - Eric Nguyen; Michael Poli; Marjan Faizi; Armin W. Thomas; Michael Wornow; Callum Birch-Sykes; Stefano Massaroli; Aman Patel; Clayton M. Rabideau; Yoshua Bengio; Stefano Ermon; Christopher Ré; et al. (NeurIPS, 2023)

SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. - Mélisande Teng; Amna Elmustafa; Benjamin Akera; Yoshua Bengio; Hager Radi Abdelwahed; Hugo Larochelle; David Rolnick (NeurIPS, 2023)

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. - Dinghuai Zhang; Hanjun Dai; Nikolay Malkin; Aaron C. Courville; Yoshua Bengio; Ling Pan (NeurIPS, 2023)

Stochastic Generative Flow Networks. - Ling Pan; Dinghuai Zhang; Moksh Jain; Longbo Huang; Yoshua Bengio (UAI, 2023)

MixupE: Understanding and improving Mixup from directional derivative perspective. - Yingtian Zou; Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham 001; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (UAI, 2023)

Leveraging the Third Dimension in Contrastive Learning. - Sumukh K. Aithal; Anirudh Goyal; Alex Lamb; Yoshua Bengio; Michael Mozer (CoRR, 2023)

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. - Alexander Tong 001; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Kilian Fatras; Guy Wolf; Yoshua Bengio (CoRR, 2023)

GFlowNets for AI-Driven Scientific Discovery. - Moksh Jain; Tristan Deleu; Jason S. Hartford; Cheng-Hao Liu; Alex Hernández-García; Yoshua Bengio (CoRR, 2023)

DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks. - Lazar Atanackovic; Alexander Tong 001; Jason S. Hartford; Leo J. Lee; Bo Wang; Yoshua Bengio (CoRR, 2023)

Sources of Richness and Ineffability for Phenomenally Conscious States. - Xu Ji; Eric Elmoznino; George Deane; Axel Constant; Guillaume Dumas; Guillaume Lajoie; Jonathan Simon; Yoshua Bengio (CoRR, 2023)

Constant Memory Attentive Neural Processes. - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2023)

Model evaluation for extreme risks. - Toby Shevlane; Sebastian Farquhar; Ben Garfinkel; Mary Phuong; Jess Whittlestone; Jade Leung; Daniel Kokotajlo; Nahema Marchal; Markus Anderljung; Noam Kolt; Lewis Ho; Divya Siddarth; et al. (CoRR, 2023)

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. - Dinghuai Zhang; Hanjun Dai; Nikolay Malkin; Aaron C. Courville; Yoshua Bengio; Ling Pan (CoRR, 2023)

Attention Schema in Neural Agents. - Dianbo Liu; Samuele Bolotta; He Zhu; Yoshua Bengio; Guillaume Dumas (CoRR, 2023)

Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. - Ayush Chakravarthy; Bailey Trang Nguyen; Anirudh Goyal; Yoshua Bengio; Michael C. Mozer (CoRR, 2023)

What if We Enrich day-ahead Solar Irradiance Time Series Forecasting with Spatio-Temporal Context? - Oussama Boussif; Ghait Boukachab; Dan Assouline; Stefano Massaroli; Tianle Yuan; Loubna Benabbou; Yoshua Bengio (CoRR, 2023)

Constant Memory Attention Block. - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2023)

BatchGFN: Generative Flow Networks for Batch Active Learning. - Shreshth A. Malik; Salem Lahlou; Andrew Jesson; Moksh Jain; Nikolay Malkin; Tristan Deleu; Yoshua Bengio; Yarin Gal (CoRR, 2023)

Thompson sampling for improved exploration in GFlowNets. - Jarrid Rector-Brooks; Kanika Madan; Moksh Jain; Maksym Korablyov; Cheng-Hao Liu; Sarath Chandar; Nikolay Malkin; Yoshua Bengio (CoRR, 2023)

Generative Flow Networks: a Markov Chain Perspective. - Tristan Deleu; Yoshua Bengio (CoRR, 2023)

International Institutions for Advanced AI. - Lewis Ho; Joslyn Barnhart; Robert Trager; Yoshua Bengio; Miles Brundage; Allison Carnegie; Rumman Chowdhury; Allan Dafoe; Gillian K. Hadfield; Margaret Levi; Duncan Snidal (CoRR, 2023)

Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. - Chris Chinenye Emezue; Alexandre Drouin; Tristan Deleu; Stefan Bauer; Yoshua Bengio (CoRR, 2023)

AI For Global Climate Cooperation 2023 Competition Proceedings. - Yoshua Bengio; Prateek Gupta; Lu Li; Soham Phade; Sunil Srinivasa; Andrew Williams; Tianyu Zhang; Yang Zhang; Stephan Zheng (CoRR, 2023)

Consciousness in Artificial Intelligence: Insights from the Science of Consciousness. - Patrick Butlin; Robert Long; Eric Elmoznino; Yoshua Bengio; Jonathan Birch; Axel Constant; George Deane; Stephen M. Fleming; Chris Frith; Xu Ji; Ryota Kanai; Colin Klein; et al. (CoRR, 2023)

Combining Spatial and Temporal Abstraction in Planning for Better Generalization. - Mingde Zhao 001; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (CoRR, 2023)

Discrete, compositional, and symbolic representations through attractor dynamics. - Andrew Nam; Eric Elmoznino; Nikolay Malkin; Chen Sun 007; Yoshua Bengio; Guillaume Lajoie (CoRR, 2023)

Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks. - Luca Scimeca; Alexander Rubinstein 002; Armand Mihai Nicolicioiu; Damien Teney; Yoshua Bengio (CoRR, 2023)

Learning to Scale Logits for Temperature-Conditional GFlowNets. - Minsu Kim 004; Joohwan Ko; Dinghuai Zhang; Ling Pan; Taeyoung Yun; Woochang Kim; Jinkyoo Park; Yoshua Bengio (CoRR, 2023)

Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. - Bailey Trang Nguyen; Alexander Tong 001; Kanika Madan; Yoshua Bengio; Dianbo Liu (CoRR, 2023)

Crystal-GFN: sampling crystals with desirable properties and constraints. - Alex Hernández-García; Alexandre Duval; Alexandra Volokhova; Yoshua Bengio; Divya Sharma; Pierre Luc Carrier; Michal Koziarski; Victor Schmidt (CoRR, 2023)

On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. - Alvaro Carbonero; Alexandre Duval; Victor Schmidt; Santiago Miret; Alex Hernández-García; Yoshua Bengio; David Rolnick (CoRR, 2023)

A cry for help: Early detection of brain injury in newborns. - Charles C. Onu; Samantha Latremouille; Arsenii Gorin; Junhao Wang; Uchenna Ekwochi; Peter O. Ubuane; Omolara A. Kehinde; Muhammad A. Salisu; Datonye Briggs; Yoshua Bengio; Doina Precup (CoRR, 2023)

Towards equilibrium molecular conformation generation with GFlowNets. - Alexandra Volokhova; Michal Koziarski; Alex Hernández-García; Cheng-Hao Liu; Santiago Miret; Pablo Lemos; Luca A. Thiede; Zichao Yan; Alán Aspuru-Guzik; Yoshua Bengio (CoRR, 2023)

Causal machine learning for single-cell genomics. - Alejandro Tejada-Lapuerta; Paul Bertin; Stefan Bauer; Hananeh Aliee; Yoshua Bengio; Fabian J. Theis (CoRR, 2023)

Managing AI Risks in an Era of Rapid Progress. - Yoshua Bengio; Geoffrey E. Hinton; Andrew Yao; Dawn Song; Pieter Abbeel; Yuval Noah Harari; Ya-Qin Zhang; Lan Xue; Shai Shalev-Shwartz; Gillian K. Hadfield; Jeff Clune; Tegan Maharaj; et al. (CoRR, 2023)

OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning. - Rim Assouel; Pau Rodríguez; Perouz Taslakian; David Vázquez 001; Yoshua Bengio (CoRR, 2023)

SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data. - Mélisande Teng; Amna Elmustafa; Benjamin Akera; Yoshua Bengio; Hager Radi Abdelwahed; Hugo Larochelle; David Rolnick (CoRR, 2023)

Unlearning via Sparse Representations. - Vedant Shah; Frederik Träuble; Ashish Malik; Hugo Larochelle; Michael Mozer; Sanjeev Arora; Yoshua Bengio; Anirudh Goyal (CoRR, 2023)

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models. - Luca Scimeca; Alexander Rubinstein 002; Damien Teney; Seong Joon Oh; Armand Mihai Nicolicioiu; Yoshua Bengio (CoRR, 2023)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. - Alexandre Duval; Simon V. Mathis; Chaitanya K. Joshi; Victor Schmidt; Santiago Miret; Fragkiskos D. Malliaros; Taco Cohen; Pietro Lio; Yoshua Bengio; Michael M. Bronstein (CoRR, 2023)

Tackling Climate Change with Machine Learning. - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Sasha Luccioni; Tegan Maharaj; et al. (ACM Comput. Surv., 2023)

GFlowNet Foundations. - Yoshua Bengio; Salem Lahlou; Tristan Deleu; Edward J. Hu; Mo Tiwari; Emmanuel Bengio (J. Mach. Learn. Res., 2023)

Benchmarking Graph Neural Networks. - Vijay Prakash Dwivedi; Chaitanya K. Joshi; Anh Tuan Luu; Thomas Laurent 001; Yoshua Bengio; Xavier Bresson (J. Mach. Learn. Res., 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Neural Causal Structure Discovery from Interventions. - Nan Rosemary Ke; Olexa Bilaniuk; Anirudh Goyal; Stefan Bauer; Hugo Larochelle; Bernhard Schölkopf; Michael Curtis Mozer; Christopher Pal; Yoshua Bengio (Trans. Mach. Learn. Res., 2023)

DEUP: Direct Epistemic Uncertainty Prediction. - Salem Lahlou; Moksh Jain; Hadi Nekoei; Victor Butoi; Paul Bertin; Jarrid Rector-Brooks; Maksym Korablyov; Yoshua Bengio (Trans. Mach. Learn. Res., 2023)

Generative AI models should include detection mechanisms as a condition for public release. - Alistair Knott; Dino Pedreschi; Raja Chatila 001; Tapabrata Chakraborti; Susan Leavy; Ricardo Baeza-Yates; David M. Eyers; Andrew Trotman; Paul D. Teal; Przemyslaw Biecek; Stuart Russell 001; Yoshua Bengio (Ethics Inf. Technol., 2023)

Regeneration Learning: A Learning Paradigm for Data Generation. - Xu Tan 003; Tao Qin 001; Jiang Bian 002; Tie-Yan Liu; Yoshua Bengio (AAAI, 2024)

Simulation-Free Schrödinger Bridges via Score and Flow Matching. - Alexander Tong 001; Nikolay Malkin; Kilian Fatras; Lazar Atanackovic; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Yoshua Bengio (AISTATS, 2024)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning. - Harry Zhao 001; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (ICLR, 2024)

Cycle Consistency Driven Object Discovery. - Aniket Rajiv Didolkar; Anirudh Goyal; Yoshua Bengio (ICLR, 2024)

Delta-AI: Local objectives for amortized inference in sparse graphical models. - Jean-Pierre R. Falet; Hae Beom Lee; Nikolay Malkin; Chen Sun 007; Dragos Secrieru; Dinghuai Zhang; Guillaume Lajoie; Yoshua Bengio (ICLR, 2024)

Tree Cross Attention. - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (ICLR, 2024)

Amortizing intractable inference in large language models. - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (ICLR, 2024)

Expected flow networks in stochastic environments and two-player zero-sum games. - Marco Jiralerspong; Bilun Sun; Danilo Vucetic; Tianyu Zhang; Yoshua Bengio; Gauthier Gidel; Nikolay Malkin (ICLR, 2024)

Local Search GFlowNets. - Minsu Kim 004; Taeyoung Yun; Emmanuel Bengio; Dinghuai Zhang; Yoshua Bengio; Sungsoo Ahn; Jinkyoo Park (ICLR, 2024)

Object centric architectures enable efficient causal representation learning. - Amin Mansouri; Jason S. Hartford; Yan Zhang 067; Yoshua Bengio (ICLR, 2024)

Pre-Training and Fine-Tuning Generative Flow Networks. - Ling Pan; Moksh Jain; Kanika Madan; Yoshua Bengio (ICLR, 2024)

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. - Dinghuai Zhang; Ricky T. Q. Chen; Cheng-Hao Liu; Aaron C. Courville; Yoshua Bengio (ICLR, 2024)

PhyloGFN: Phylogenetic inference with generative flow networks. - Ming-Yang Zhou; Zichao Yan; Elliot Layne; Nikolay Malkin; Dinghuai Zhang; Moksh Jain; Mathieu Blanchette; Yoshua Bengio (ICLR, 2024)

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. - Tara Akhound-Sadegh; Jarrid Rector-Brooks; Avishek Joey Bose; Sarthak Mittal; Pablo Lemos; Cheng-Hao Liu; Marcin Sendera; Siamak Ravanbakhsh; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Alexander Tong 001 (ICML, 2024)

Memory Efficient Neural Processes via Constant Memory Attention Block. - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (ICML, 2024)

Learning to Scale Logits for Temperature-Conditional GFlowNets. - Minsu Kim 004; Joohwan Ko; Taeyoung Yun; Dinghuai Zhang; Ling Pan; Woochang Kim; Jinkyoo Park; Emmanuel Bengio; Yoshua Bengio (ICML, 2024)

Improving Gradient-Guided Nested Sampling for Posterior Inference. - Pablo Lemos; Nikolay Malkin; Will Handley; Yoshua Bengio; Yashar Hezaveh; Laurence Perreault Levasseur (ICML, 2024)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Omar Mohamed Awad; Isak Edo Vivancos; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (ISCAS, 2024)

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Siyuan Guo; Michal Valko; Timothy P. Lillicrap; Danilo Jimenez Rezende; Yoshua Bengio; Michael C. Mozer; Sanjeev Arora (NeurIPS, 2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets. - Michal Koziarski; Andrei Rekesh; Dmytro Shevchuk; Almer van der Sloot; Piotr Gainski; Yoshua Bengio; Cheng-Hao Liu; Mike Tyers; Robert A. Batey (NeurIPS, 2024)

Improved off-policy training of diffusion samplers. - Marcin Sendera; Minsu Kim 004; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (NeurIPS, 2024)

Amortizing intractable inference in diffusion models for vision, language, and control. - Siddarth Venkatraman; Moksh Jain; Luca Scimeca; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (NeurIPS, 2024)

Trajectory Flow Matching with Applications to Clinical Time Series Modelling. - Xi Zhang; Yuan Pu 002; Yuki Kawamura; Andrew Loza; Yoshua Bengio; Dennis L. Shung; Alexander Tong 001 (NeurIPS, 2024)

Discrete Probabilistic Inference as Control in Multi-path Environments. - Tristan Deleu; Padideh Nouri; Nikolay Malkin; Doina Precup; Yoshua Bengio (UAI, 2024)

Efficient Causal Graph Discovery Using Large Language Models. - Thomas Jiralerspong; Xiaoyin Chen; Yash More; Vedant Shah; Yoshua Bengio (CoRR, 2024)

On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. - Marcin Sendera; Minsu Kim 004; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (CoRR, 2024)

Computing Power and the Governance of Artificial Intelligence. - Girish Sastry; Lennart Heim; Haydn Belfield; Markus Anderljung; Miles Brundage; Julian Hazell; Cullen O'Keefe; Gillian K. Hadfield; Richard Ngo; Konstantin Pilz; George Gor; Emma Bluemke; et al. (CoRR, 2024)

Machine learning and information theory concepts towards an AI Mathematician. - Yoshua Bengio; Nikolay Malkin (CoRR, 2024)

Language Models Can Reduce Asymmetry in Information Markets. - Nasim Rahaman; Martin Weiss; Manuel Wüthrich; Yoshua Bengio; Li Erran Li; Chris Pal; Bernhard Schölkopf (CoRR, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (CoRR, 2024)

Towards DNA-Encoded Library Generation with GFlowNets. - Michal Koziarski; Mohammed Abukalam; Vedant Shah; Louis Vaillancourt; Doris Alexandra Schuetz; Moksh Jain; Almer van der Sloot; Mathieu Bourgey; Anne Marinier; Yoshua Bengio (CoRR, 2024)

Generative Active Learning for the Search of Small-molecule Protein Binders. - Maksym Korablyov; Cheng-Hao Liu; Moksh Jain; Almer M. van der Sloot; Eric Jolicoeur; Edward Ruediger; Andrei Cristian Nica; Emmanuel Bengio; Kostiantyn Lapchevskyi; Daniel St-Cyr; Doris Alexandra Schuetz; Victor Ion Butoi; et al. (CoRR, 2024)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell 001; Max Tegmark; Sanjit Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (CoRR, 2024)

Divergent Creativity in Humans and Large Language Models. - Antoine Bellemare-Pépin; François Lespinasse; Philipp Thölke; Yann Harel; Kory W. Mathewson; Jay A. Olson; Yoshua Bengio; Karim Jerbi (CoRR, 2024)

Attention as an RNN. - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Mohamed Osama Ahmed; Yoshua Bengio; Greg Mori (CoRR, 2024)

Baking Symmetry into GFlowNets. - George Ma; Emmanuel Bengio; Yoshua Bengio; Dinghuai Zhang (CoRR, 2024)

VCR: Visual Caption Restoration. - Tianyu Zhang; Suyuchen Wang; Lu Li; Ge Zhang 009; Perouz Taslakian; Sai Rajeswar; Jie Fu 001; Bang Liu; Yoshua Bengio (CoRR, 2024)

On Generalization for Generative Flow Networks. - Anas Krichel; Nikolay Malkin; Salem Lahlou; Yoshua Bengio (CoRR, 2024)

Open Problems in Technical AI Governance. - Anka Reuel; Ben Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (CoRR, 2024)

AI-Assisted Generation of Difficult Math Questions. - Vedant Shah; Dingli Yu; Kaifeng Lyu; Simon Park 002; Nan Rosemary Ke; Michael Mozer; Yoshua Bengio; Sanjeev Arora; Anirudh Goyal (CoRR, 2024)

Cell Morphology-Guided Small Molecule Generation with GFlowNets. - Stephen Zhewen Lu; Ziqing Lu; Ehsan Hajiramezanali; Tommaso Biancalani; Yoshua Bengio; Gabriele Scalia; Michal Koziarski (CoRR, 2024)

Zero-Shot Object-Centric Representation Learning. - Aniket Didolkar; Andrii Zadaianchuk; Anirudh Goyal; Michael C. Mozer; Yoshua Bengio; Georg Martius; Maximilian Seitzer (CoRR, 2024)

Were RNNs All We Needed? - Leo Feng; Frederick Tung; Mohamed Osama Ahmed; Yoshua Bengio; Hossein Hajimirsadeghi (CoRR, 2024)

Identifying and Addressing Delusions for Target-Directed Decision-Making. - Mingde Zhao 001; Tristan Sylvain; Doina Precup; Yoshua Bengio (CoRR, 2024)

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. - Jarrid Rector-Brooks; Mohsin Hasan; Zhangzhi Peng; Zachary Quinn; Cheng-Hao Liu; Sarthak Mittal; Nouha Dziri; Michael M. Bronstein; Yoshua Bengio; Pranam Chatterjee; Alexander Tong 001; Avishek Joey Bose (CoRR, 2024)

A Complexity-Based Theory of Compositionality. - Eric Elmoznino; Thomas Jiralerspong; Yoshua Bengio; Guillaume Lajoie (CoRR, 2024)

Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases. - Cristian Meo; Akihiro Nakano; Mircea Lica; Aniket Didolkar; Masahiro Suzuki 001; Anirudh Goyal; Mengmi Zhang; Justin Dauwels; Yutaka Matsuo; Yoshua Bengio (CoRR, 2024)

Trajectory Flow Matching with Applications to Clinical Time Series Modeling. - Xi Zhang; Yuan Pu 002; Yuki Kawamura; Andrew Loza; Yoshua Bengio; Dennis L. Shung; Alexander Tong 001 (CoRR, 2024)

Imagining and building wise machines: The centrality of AI metacognition. - Samuel G. B. Johnson; Amir-Hossein Karimi; Yoshua Bengio; Nick Chater; Tobias Gerstenberg; Kate Larson; Sydney Levine; Melanie Mitchell; Iyad Rahwan; Bernhard Schölkopf; Igor Grossmann (CoRR, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

International Scientific Report on the Safety of Advanced AI (Interim Report). - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Danielle Goldfarb; Hoda Heidari; Leila Khalatbari; Shayne Longpre; Vasilios Mavroudis; et al. (CoRR, 2024)

PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design. - Alexandre Duval; Victor Schmidt; Santiago Miret; Yoshua Bengio; Alex Hernández-García; David Rolnick (J. Mach. Learn. Res., 2024)

Improving and generalizing flow-based generative models with minibatch optimal transport. - Alexander Tong 001; Kilian Fatras; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Guy Wolf; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (Trans. Mach. Learn. Res., 2024)

Multi-Fidelity Active Learning with GFlowNets. - Alex Hernández-García; Nikita Saxena; Moksh Jain; Cheng-Hao Liu; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Distributional GFlowNets with Quantile Flows. - Dinghuai Zhang; Ling Pan; Ricky T. Q. Chen; Aaron C. Courville; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Geometric Signatures of Compositionality Across a Language Model's Lifetime. - Jin Hwa Lee; Thomas Jiralerspong; Lei Yu; Yoshua Bengio; Emily Cheng (ACL (1), 2025)

Ant Colony Sampling with GFlowNets for Combinatorial Optimization. - Minsu Kim 004; Sanghyeok Choi; Hyeonah Kim; Jiwoo Son; Jinkyoo Park; Yoshua Bengio (AISTATS, 2025)

Adaptive teachers for amortized samplers. - Minsu Kim 004; Sanghyeok Choi; Taeyoung Yun; Emmanuel Bengio; Leo Feng; Jarrid Rector-Brooks; Sungsoo Ahn; Jinkyoo Park; Nikolay Malkin; Yoshua Bengio (ICLR, 2025)

Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. - Lazar Atanackovic; Xi Zhang; Brandon Amos; Mathieu Blanchette; Leo J. Lee; Yoshua Bengio; Alexander Tong 001; Kirill Neklyudov (ICLR, 2025)

Action abstractions for amortized sampling. - Oussama Boussif; Léna Néhale Ezzine; Joseph D. Viviano; Michal Koziarski; Moksh Jain; Nikolay Malkin; Emmanuel Bengio; Rim Assouel; Yoshua Bengio (ICLR, 2025)

On the Transfer of Object-Centric Representation Learning. - Aniket Rajiv Didolkar; Andrii Zadaianchuk; Anirudh Goyal; Michael Curtis Mozer; Yoshua Bengio; Georg Martius; Maximilian Seitzer (ICLR, 2025)

AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly. - Hongyu Guo; Yoshua Bengio; Shengchao Liu (ICLR, 2025)

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. - Seanie Lee; Minsu Kim 004; Lynn Cherif; David Dobre; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (ICLR, 2025)

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. - Seanie Lee; Haebin Seong; Dong Bok Lee; Minki Kang; Xiaoyin Chen; Dominik Wagner 002; Yoshua Bengio; Juho Lee 001; Sung Ju Hwang (ICLR, 2025)

MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation. - Lu Li; Tianyu Zhang; Zhiqi Bu; Suyuchen Wang; Huan He; Jie Fu 001; Yonghui Wu; Jiang Bian 002; Yong Chen 016; Yoshua Bengio (ICLR, 2025)

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. - Zhen Liu 019; Tim Z. Xiao; Weiyang Liu; Yoshua Bengio; Dinghuai Zhang (ICLR, 2025)

Structure Language Models for Protein Conformation Generation. - Jiarui Lu; Xiaoyin Chen; Stephen Zhewen Lu; Chence Shi; Hongyu Guo; Yoshua Bengio; Jian Tang 005 (ICLR, 2025)

Towards Improving Exploration through Sibling Augmented GFlowNets. - Kanika Madan; Alex Lamb; Emmanuel Bengio; Glen Berseth; Yoshua Bengio (ICLR, 2025)

VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text. - Tianyu Zhang; Suyuchen Wang; Lu Li; Ge Zhang 009; Perouz Taslakian; Sai Rajeswar; Jie Fu 001; Bang Liu; Yoshua Bengio (ICLR, 2025)

Can a Bayesian Oracle Prevent Harm from an Agent? - Yoshua Bengio; Michael K. Cohen; Nikolay Malkin; Matt MacDermott; Damiano Fornasiere; Pietro Greiner; Younesse Kaddar (UAI, 2025)

RL, but don't do anything I wouldn't do. - Michael K. Cohen; Marcus Hutter; Yoshua Bengio; Stuart Russell 001 (UAI, 2025)

EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision. - Diego A. Velázquez; Pau Rodríguez López; Sergio Alonso; Josep M. Gonfaus; Jordi Gonzàlez 001; Gerardo Richarte; Javier Marin; Yoshua Bengio; Alexandre Lacoste (WACV (Workshops), 2025)

Open Problems in Technical AI Governance. - Anka Reuel; Benjamin Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (Trans. Mach. Learn. Res., 2025)

Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity. - David Williams-King; Linh Le; Adam Oberman; Yoshua Bengio (CoRR, 2025)

International AI Safety Report. - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Philip Fox; Ben Garfinkel; Danielle Goldfarb; Hoda Heidari; Anson Ho; et al. (CoRR, 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding. - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (CoRR, 2025)

A physics-based data-driven model for CO2 gas diffusion electrodes to drive automated laboratories. - Ivan Grega; Félix Therrien; Abhishek Soni; Karry Ocean; Kevan Dettelbach; Ribwar Ahmadi; Mehrdad Mokhtari; Curtis P. Berlinguette; Yoshua Bengio (CoRR, 2025)

Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models. - Siddarth Venkatraman; Mohsin Hasan; Minsu Kim 004; Luca Scimeca; Marcin Sendera; Yoshua Bengio; Glen Berseth; Nikolay Malkin (CoRR, 2025)

Monte Carlo Tree Diffusion for System 2 Planning. - Jaesik Yoon; Hyeonseo Cho; Doojin Baek; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control. - Thomas Jiralerspong; Berton Earnshaw; Jason S. Hartford; Yoshua Bengio; Luca Scimeca (CoRR, 2025)

In-Context Parametric Inference: Point or Distribution Estimators? - Sarthak Mittal; Yoshua Bengio; Nikolay Malkin; Guillaume Lajoie (CoRR, 2025)

OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes. - Félix Therrien; Jamal Abou Haibeh; Divya Sharma; Rhiannon Hendley; Alex Hernández-García; Sun Sun; Alain Tchagang; Jiang Su; Samuel Huberman; Yoshua Bengio; Hongyu Guo; Homin Shin (CoRR, 2025)

Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path? - Yoshua Bengio; Michael K. Cohen; Damiano Fornasiere; Joumana Ghosn; Pietro Greiner; Matt MacDermott; Sören Mindermann; Adam Oberman; Jesse Richardson; Oliver Richardson; Marc-Antoine Rondeau; Pierre-Luc St-Charles; et al. (CoRR, 2025)

Learning Decision Trees as Amortized Structure Inference. - Mohammed Mahfoud; Ghait Boukachab; Michal Koziarski; Alex Hernández-García; Stefan Bauer; Yoshua Bengio; Nikolay Malkin (CoRR, 2025)

Solving Bayesian inverse problems with diffusion priors and off-policy RL. - Luca Scimeca; Siddarth Venkatraman; Moksh Jain; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (CoRR, 2025)

Offline Model-Based Optimization: Comprehensive Review. - Minsu Kim 004; Jiayao Gu; Ye Yuan 017; Taeyoung Yun; Zixuan Liu 001; Yoshua Bengio; Can Chen 005 (CoRR, 2025)

Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. - Brian R. Bartoldson; Siddarth Venkatraman; James Diffenderfer; Moksh Jain; Tal Ben-Nun; Seanie Lee; Minsu Kim 004; Johan S. Obando-Ceron; Yoshua Bengio; Bhavya Kailkhura (CoRR, 2025)

A scalable gene network model of regulatory dynamics in single cells. - Paul Bertin; Joseph D. Viviano; Alejandro Tejada-Lapuerta; Weixu Wang; Stefan Bauer; Fabian J. Theis; Yoshua Bengio (CoRR, 2025)

Extendable Long-Horizon Planning via Hierarchical Multiscale Diffusion. - Chang Chen; Hany Hamed; Doojin Baek; Taegu Kang; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery. - Mélisande Teng; Arthur Ouaknine; Etienne Laliberté; Yoshua Bengio; David Rolnick; Hugo Larochelle (CoRR, 2025)

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? - Ben Bucknall; Saad Siddiqui; Lara Thurnherr; Conor McGurk; Ben Harack; Anka Reuel; Patricia Paskov; Casey Mahoney; Sören Mindermann; Scott Singer; Vinay Hiremath; Charbel-Raphaël Ségerie; et al. (CoRR, 2025)

Search-Based Correction of Reasoning Chains for Language Models. - Minsu Kim 004; Jean-Pierre R. Falet; Oliver E. Richardson; Xiaoyin Chen; Moksh Jain; Sungjin Ahn; Sungsoo Ahn; Yoshua Bengio (CoRR, 2025)

Adaptive Cyclic Diffusion for Inference Scaling. - Gyubin Lee; Truong Nhat Nguyen Bao; Jaesik Yoon; Dongwoo Lee; Minsu Kim 004; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Self-Evolving Curriculum for LLM Reasoning. - Xiaoyin Chen; Jiarui Lu; Minsu Kim 004; Dinghuai Zhang; Jian Tang 005; Alexandre Piché; Nicolas Gontier; Yoshua Bengio; Ehsan Kamalloo (CoRR, 2025)

Structure-Aligned Protein Language Model. - Can Chen 005; David Heurtel-Depeiges; Robert M. Vernon; Christopher James Langmead; Yoshua Bengio; Quentin Fournier (CoRR, 2025)

FORT: Forward-Only Regression Training of Normalizing Flows. - Danyal Rehman; Oscar Davis; Jiarui Lu; Jian Tang 005; Michael M. Bronstein; Yoshua Bengio; Alexander Tong 001; Avishek Joey Bose (CoRR, 2025)

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery. - Mélisande Teng; Arthur Ouaknine; Etienne Laliberté; Yoshua Bengio; David Rolnick; Hugo Larochelle (CoRR, 2025)

Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning. - Jaesik Yoon; Hyeonseo Cho; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. - Tomek Korbak; Mikita Balesni; Elizabeth Barnes; Yoshua Bengio; Joe Benton; Joseph Bloom; Mark Chen 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)

Torsional-GFN: a conditional conformation generator for small molecules. - Alexandra Volokhova; Léna Néhale Ezzine; Piotr Gainski; Luca Scimeca; Emmanuel Bengio; Prudencio Tossou; Yoshua Bengio; Alex Hernández-García (CoRR, 2025)

Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization. - Shengchao Liu; Hannan Xu; Yan Ai; Huanxin Li; Yoshua Bengio; Harry Guo (CoRR, 2025)