Region Tracking through Neural Classifier. - Patrick Thévenoux; Pascal Vincent (MVA, 1990)

Color Documents on the Web with DJVU. - Patrick Haffner; Yann LeCun; Léon Bottou; Paul G. Howard; Pascal Vincent; Bill Riemers (ICIP (1), 1999)

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)

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)

ROBOSIX UPMC-CFA: RoboCup Team Description. - Ryad Benosman; Francis Bras; Frederic Bach; Simon Boulay; Emmanuelle Cahn; Sylvain Come; Gilles Cordurié; Jarlegan Marie Annick; Lapied Loic; Cyrille Potereau; Franck Richard; Samedi Sath; et al. (RoboCup, 2001)

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

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

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)

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

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)

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)

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

The Need for Open Source Software in Machine Learning. - Sören Sonnenburg; Mikio L. Braun; Cheng Soon Ong; Samy Bengio; Léon Bottou; Geoffrey Holmes 001; Yann LeCun; Klaus-Robert Müller; Fernando Pereira 003; Carl Edward Rasmussen; Gunnar Rätsch; Bernhard Schölkopf; et al. (J. Mach. Learn. Res., 2007)

Scoring Models for Insurance Risk Sharing Pool Opimization. - Nicolas Chapados; Charles Dugas; Pascal Vincent; Réjean Ducharme (ICDM Workshops, 2008)

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

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)

Deep Learning using Robust Interdependent Codes. - Hugo Larochelle; Dumitru Erhan; Pascal Vincent (AISTATS, 2009)

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)

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)

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

Fabrication and characterization of 100-nm wide silicon nanocantilevers using top-down approach. - Samuel Guillon; Daisuke Saya; Laurent Mazenq; Liviu Nicu; Sorin Perisanu; Pascal Vincent (NEMS, 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)

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)

A high-order feature synthesis and selection algorithm applied to insurance risk modelling. - Charles Dugas; Nicolas Chapados; Réjean Ducharme; Xavier Saint-Mleux; Pascal Vincent (Int. J. Bus. Intell. Data Min., 2011)

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

A Connection Between Score Matching and Denoising Autoencoders. - Pascal Vincent (Neural Comput., 2011)

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)

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)

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

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)

Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction. - Hani Almousli; Pascal Vincent (ICONIP (1), 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)

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)

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

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. - Pascal Vincent; Alexandre de Brébisson; Xavier Bouthillier (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)

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

Clustering is Efficient for Approximate Maximum Inner Product Search. - Alex Auvolat; Pascal Vincent (CoRR, 2015)

Dropout as data augmentation. - Kishore Reddy Konda; Xavier Bouthillier; Roland Memisevic; Pascal Vincent (CoRR, 2015)

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. - Pascal Vincent (ICLR (Workshop), 2015)

Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation. - Sina Honari; Jason Yosinski; Pascal Vincent; Christopher J. Pal (CVPR, 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)

An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family. - Alexandre de Brébisson; Pascal Vincent (ICLR (Poster), 2016)

A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations. - Alexandre de Brébisson; Pascal Vincent (CoRR, 2016)

The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family. - Alexandre de Brébisson; Pascal Vincent (CoRR, 2016)

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

Exact gradient updates in time independent of output size for the spherical loss family. - Pascal Vincent; Alexandre de Brébisson; Xavier Bouthillier (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)

RATM: Recurrent Attentive Tracking Model. - Samira Ebrahimi Kahou; Vincent Michalski; Roland Memisevic; Christopher Joseph Pal; Pascal Vincent (CVPR Workshops, 2017)

Learning to Generate Samples from Noise through Infusion Training. - Florian Bordes; Sina Honari; Pascal Vincent (ICLR (Poster), 2017)

Recurrent Normalization Propagation. - César Laurent; Nicolas Ballas; Pascal Vincent (ICLR (Workshop), 2017)

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

Improving Landmark Localization With Semi-Supervised Learning. - Sina Honari; Pavlo Molchanov 001; Stephen Tyree; Pascal Vincent; Christopher J. Pal; Jan Kautz (CVPR, 2018)

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings. - Tom Bosc; Pascal Vincent (EMNLP, 2018)

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. - Gabriel Huang; Hugo Berard; Ahmed Touati; Gauthier Gidel; Pascal Vincent; Simon Lacoste-Julien (ICLR (Workshop), 2018)

An Evaluation of Fisher Approximations Beyond Kronecker Factorization. - César Laurent; Thomas George; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (ICLR (Workshop), 2018)

Convergent TREE BACKUP and RETRACE with Function Approximation. - Ahmed Touati; Pierre-Luc Bacon; Doina Precup; Pascal Vincent (ICML, 2018)

Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis. - Thomas George; César Laurent; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (NeurIPS, 2018)

A Variational Inequality Perspective on Generative Adversarial Nets. - Gauthier Gidel; Hugo Berard; Pascal Vincent; Simon Lacoste-Julien (CoRR, 2018)

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. - Jure Zbontar; Florian Knoll; Anuroop Sriram; Matthew J. Muckley; Mary Bruno; Aaron Defazio; Marc Parente; Krzysztof J. Geras; Joe Katsnelson; Hersh Chandarana; Zizhao Zhang; Michal Drozdzal; et al. (CoRR, 2018)

Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition. - Zizhao Zhang; Adriana Romero; Matthew J. Muckley; Pascal Vincent; Lin Yang 002; Michal Drozdzal (CVPR, 2019)

A Variational Inequality Perspective on Generative Adversarial Networks. - Gauthier Gidel; Hugo Berard; Gaëtan Vignoud; Pascal Vincent; Simon Lacoste-Julien (ICLR (Poster), 2019)

Unreproducible Research is Reproducible. - Xavier Bouthillier; César Laurent; Pascal Vincent (ICML, 2019)

Randomized Value Functions via Multiplicative Normalizing Flows. - Ahmed Touati; Harsh Satija; Joshua Romoff; Joelle Pineau; Pascal Vincent (UAI, 2019)

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation. - Vincent Michalski; Vikram Voleti; Samira Ebrahimi Kahou; Anthony Ortiz; Pascal Vincent; Chris Pal; Doina Precup (CoRR, 2019)

Stochastic Neural Network with Kronecker Flow. - Chin-Wei Huang; Ahmed Touati; Pascal Vincent; Gintare Karolina Dziugaite; Alexandre Lacoste; Aaron C. Courville (AISTATS, 2020)

Do sequence-to-sequence VAEs learn global features of sentences? - Tom Bosc; Pascal Vincent (EMNLP (1), 2020)

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. - Hugo Berard; Gauthier Gidel; Amjad Almahairi; Pascal Vincent; Simon Lacoste-Julien (ICLR, 2020)

Stochastic Hamiltonian Gradient Methods for Smooth Games. - Nicolas Loizou; Hugo Berard; Alexia Jolicoeur-Martineau; Pascal Vincent; Simon Lacoste-Julien; Ioannis Mitliagkas (ICML, 2020)

SVRG for Policy Evaluation with Fewer Gradient Evaluations. - Zilun Peng; Ahmed Touati; Pascal Vincent; Doina Precup (IJCAI, 2020)

Adversarial Example Games. - Avishek Joey Bose; Gauthier Gidel; Hugo Berard; Andre Cianflone; Pascal Vincent; Simon Lacoste-Julien; William L. Hamilton (NeurIPS, 2020)

Stable Policy Optimization via Off-Policy Divergence Regularization. - Ahmed Touati; Amy Zhang 001; Joelle Pineau; Pascal Vincent (UAI, 2020)

Revisiting Loss Modelling for Unstructured Pruning. - César Laurent; Camille Ballas; Thomas George; Nicolas Ballas; Pascal Vincent (CoRR, 2020)

Sharp Analysis of Smoothed Bellman Error Embedding. - Ahmed Touati; Pascal Vincent (CoRR, 2020)

Implicit Regularization in Deep Learning: A View from Function Space. - Aristide Baratin; Thomas George; César Laurent; R. Devon Hjelm; Guillaume Lajoie; Pascal Vincent; Simon Lacoste-Julien (CoRR, 2020)

Efficient Learning in Non-Stationary Linear Markov Decision Processes. - Ahmed Touati; Pascal Vincent (CoRR, 2020)

Implicit Regularization via Neural Feature Alignment. - Aristide Baratin; Thomas George; César Laurent; R. Devon Hjelm; Guillaume Lajoie; Pascal Vincent; Simon Lacoste-Julien (AISTATS, 2021)

Accounting for Variance in Machine Learning Benchmarks. - Xavier Bouthillier; Pierre Delaunay; Mirko Bronzi; Assya Trofimov; Brennan Nichyporuk; Justin Szeto; Nazanin Mohammadi Sepahvand; Edward Raff; Kanika Madan; Vikram Voleti; Samira Ebrahimi Kahou; Vincent Michalski; et al. (MLSys, 2021)

Accounting for Variance in Machine Learning Benchmarks. - Xavier Bouthillier; Pierre Delaunay; Mirko Bronzi; Assya Trofimov; Brennan Nichyporuk; Justin Szeto; Naz Sepah; Edward Raff; Kanika Madan; Vikram Voleti; Samira Ebrahimi Kahou; Vincent Michalski; et al. (CoRR, 2021)

Masked Siamese Networks for Label-Efficient Learning. - Mahmoud Assran; Mathilde Caron; Ishan Misra; Piotr Bojanowski; Florian Bordes; Pascal Vincent; Armand Joulin; Mike Rabbat; Nicolas Ballas (ECCV (31), 2022)

Understanding Dimensional Collapse in Contrastive Self-supervised Learning. - Li Jing 001; Pascal Vincent; Yann LeCun; Yuandong Tian (ICLR, 2022)

Online Adversarial Attacks. - Andjela Mladenovic; Avishek Joey Bose; Hugo Berard; William L. Hamilton; Simon Lacoste-Julien; Pascal Vincent; Gauthier Gidel (ICLR, 2022)

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head. - Florian Bordes; Randall Balestriero; Quentin Garrido; Adrien Bardes; Pascal Vincent (CoRR, 2022)

The Emergence of Argument Structure in Artificial Languages. - Tom Bosc; Pascal Vincent (Trans. Assoc. Comput. Linguistics, 2022)

High Fidelity Visualization of What Your Self-Supervised Representation Knows About. - Florian Bordes; Randall Balestriero; Pascal Vincent (Trans. Mach. Learn. Res., 2022)

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. - Mahmoud Assran; Quentin Duval; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Yann LeCun; Nicolas Ballas (CVPR, 2023)

The hidden uniform cluster prior in self-supervised learning. - Mido Assran; Randall Balestriero; Quentin Duval; Florian Bordes; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Nicolas Ballas (ICLR, 2023)

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. - Badr Youbi Idrissi; Diane Bouchacourt; Randall Balestriero; Ivan Evtimov; Caner Hazirbas; Nicolas Ballas; Pascal Vincent; Michal Drozdzal; David Lopez-Paz; Mark Ibrahim (ICLR, 2023)

Disentanglement of Correlated Factors via Hausdorff Factorized Support. - Karsten Roth; Mark Ibrahim; Zeynep Akata; Pascal Vincent; Diane Bouchacourt (ICLR, 2023)

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. - Florian Bordes; Shashank Shekhar; Mark Ibrahim; Diane Bouchacourt; Pascal Vincent; Ari Morcos (NeurIPS, 2023)

Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. - Casey Meehan; Florian Bordes; Pascal Vincent; Kamalika Chaudhuri; Chuan Guo 001 (NeurIPS, 2023)

Towards Democratizing Joint-Embedding Self-Supervised Learning. - Florian Bordes; Randall Balestriero; Pascal Vincent (CoRR, 2023)

Instance-Conditioned GAN Data Augmentation for Representation Learning. - Pietro Astolfi; Arantxa Casanova; Jakob Verbeek; Pascal Vincent; Adriana Romero-Soriano; Michal Drozdzal (CoRR, 2023)

A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation. - Florian Bordes; Samuel Lavoie; Randall Balestriero; Nicolas Ballas; Pascal Vincent (CoRR, 2023)

Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations. - Shashank Shekhar; Florian Bordes; Pascal Vincent; Ari Morcos (CoRR, 2023)

Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection. - Vitória Barin Pacela; Kartik Ahuja; Simon Lacoste-Julien; Pascal Vincent (CoRR, 2023)

Predicting masked tokens in stochastic locations improves masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mahmoud Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (CoRR, 2023)

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. - Cian Eastwood; Julius von Kügelgen; Linus Ericsson; Diane Bouchacourt; Pascal Vincent; Bernhard Schölkopf; Mark Ibrahim (CoRR, 2023)

WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models. - Youssef Benchekroun; Megi Dervishi; Mark Ibrahim; Jean-Baptiste Gaya; Xavier Martinet; Grégoire Mialon; Thomas Scialom; Emmanuel Dupoux; Dieuwke Hupkes; Pascal Vincent (CoRR, 2023)

Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning. - Florian Bordes; Randall Balestriero; Quentin Garrido; Adrien Bardes; Pascal Vincent (Trans. Mach. Learn. Res., 2023)

On the Identifiability of Quantized Factors. - Vitória Barin Pacela; Kartik Ahuja; Simon Lacoste-Julien; Pascal Vincent (CLeaR, 2024)

Motif: Intrinsic Motivation from Artificial Intelligence Feedback. - Martin Klissarov; Pierluca D'Oro; Shagun Sodhani; Roberta Raileanu; Pierre-Luc Bacon; Pascal Vincent; Amy Zhang 001; Mikael Henaff (ICLR, 2024)

Stochastic positional embeddings improve masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mido Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (ICML, 2024)

Discovering Environments with XRM. - Mohammad Pezeshki; Diane Bouchacourt; Mark Ibrahim; Nicolas Ballas; Pascal Vincent; David Lopez-Paz (ICML, 2024)

Compositional Risk Minimization. - Divyat Mahajan; Mohammad Pezeshki; Ioannis Mitliagkas; Kartik Ahuja; Pascal Vincent (CoRR, 2024)

The Pitfalls of Memorization: When Memorization Hurts Generalization. - Reza Bayat; Mohammad Pezeshki; Elvis Dohmatob; David Lopez-Paz; Pascal Vincent (ICLR, 2025)

MaestroMotif: Skill Design from Artificial Intelligence Feedback. - Martin Klissarov; Mikael Henaff; Roberta Raileanu; Shagun Sodhani; Pascal Vincent; Amy Zhang 001; Pierre-Luc Bacon; Doina Precup; Marlos C. Machado; Pierluca D'Oro (ICLR, 2025)

Steering Large Language Model Activations in Sparse Spaces. - Reza Bayat; Ali Rahimi-Kalahroudi; Mohammad Pezeshki; Sarath Chandar; Pascal Vincent (CoRR, 2025)