Aaron C. Courville

According to our database1, Aaron C. Courville authored at least 153 papers between 2001 and 2018.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2018
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks.
CoRR, 2018

On the Learning Dynamics of Deep Neural Networks.
CoRR, 2018

Improving Explorability in Variational Inference with Annealed Variational Objectives.
CoRR, 2018

Approximate Exploration through State Abstraction.
CoRR, 2018

Visual Reasoning with Multi-hop Feature Modulation.
CoRR, 2018

On the Spectral Bias of Deep Neural Networks.
CoRR, 2018

Learning Distributed Representations from Reviews for Collaborative Filtering.
CoRR, 2018

Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer.
CoRR, 2018

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance.
CoRR, 2018

Neural Autoregressive Flows.
CoRR, 2018

Generating Contradictory, Neutral, and Entailing Sentences.
CoRR, 2018

Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data.
CoRR, 2018

Hierarchical Adversarially Learned Inference.
CoRR, 2018

MINE: Mutual Information Neural Estimation.
CoRR, 2018

Neural Autoregressive Flows.
Proceedings of the 35th International Conference on Machine Learning, 2018

Mutual Information Neural Estimation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data.
Proceedings of the 35th International Conference on Machine Learning, 2018

Visual Reasoning with Multi-hop Feature Modulation.
Proceedings of the Computer Vision - ECCV 2018, 2018

Sim-to-Real Transfer with Neural-Augmented Robot Simulation.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

FiLM: Visual Reasoning with a General Conditioning Layer.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Brain tumor segmentation with Deep Neural Networks.
Medical Image Analysis, 2017

Movie Description.
International Journal of Computer Vision, 2017

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models.
CoRR, 2017

HoME: a Household Multimodal Environment.
CoRR, 2017

Neural Language Modeling by Jointly Learning Syntax and Lexicon.
CoRR, 2017

Bayesian Hypernetworks.
CoRR, 2017

Learnable Explicit Density for Continuous Latent Space and Variational Inference.
CoRR, 2017

FiLM: Visual Reasoning with a General Conditioning Layer.
CoRR, 2017

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks.
CoRR, 2017

Modulating early visual processing by language.
CoRR, 2017

End-to-end optimization of goal-driven and visually grounded dialogue systems.
CoRR, 2017

Self-organized Hierarchical Softmax.
CoRR, 2017

Adversarial Generation of Natural Language.
CoRR, 2017

Learning Visual Reasoning Without Strong Priors.
CoRR, 2017

Improved Training of Wasserstein GANs.
CoRR, 2017

Calibrating Energy-based Generative Adversarial Networks.
CoRR, 2017

A Closer Look at Memorization in Deep Networks.
CoRR, 2017

Adversarial Generation of Natural Language.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Modulating early visual processing by language.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Improved Training of Wasserstein GANs.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Counterpoint by Convolution.
Proceedings of the 18th International Society for Music Information Retrieval Conference, 2017

End-to-end optimization of goal-driven and visually grounded dialogue systems.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

A Closer Look at Memorization in Deep Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Piecewise Latent Variables for Neural Variational Text Processing.
Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing, 2017

Piecewise Latent Variables for Neural Variational Text Processing.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
EmoNets: Multimodal deep learning approaches for emotion recognition in video.
J. Multimodal User Interfaces, 2016

GuessWhat?! Visual object discovery through multi-modal dialogue.
CoRR, 2016

A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images.
CoRR, 2016

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues.
CoRR, 2016

Multi-modal Variational Encoder-Decoders.
CoRR, 2016

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation.
CoRR, 2016

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus.
CoRR, 2016

Movie Description.
CoRR, 2016

Generalizable Features From Unsupervised Learning.
CoRR, 2016

SampleRNN: An Unconditional End-to-End Neural Audio Generation Model.
CoRR, 2016

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering.
CoRR, 2016

Professor Forcing: A New Algorithm for Training Recurrent Networks.
CoRR, 2016

Discriminative Regularization for Generative Models.
CoRR, 2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
CoRR, 2016

PixelVAE: A Latent Variable Model for Natural Images.
CoRR, 2016

Adversarially Learned Inference.
CoRR, 2016

Recurrent Batch Normalization.
CoRR, 2016

An Actor-Critic Algorithm for Sequence Prediction.
CoRR, 2016

First Result on Arabic Neural Machine Translation.
CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
CoRR, 2016

Professor Forcing: A New Algorithm for Training Recurrent Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks.
Proceedings of the Interspeech 2016, 2016

Deconstructing the Ladder Network Architecture.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Dynamic Capacity Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep Learning Vector Quantization.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Deep Learning.
Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-03561-3, 2016

2015
Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks.
IEEE Trans. Multimedia, 2015

Challenges in representation learning: A report on three machine learning contests.
Neural Networks, 2015

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism.
CoRR, 2015

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.
CoRR, 2015

ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks.
CoRR, 2015

ReSeg: A Recurrent Neural Network for Object Segmentation.
CoRR, 2015

Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research.
CoRR, 2015

Hierarchical Neural Network Generative Models for Movie Dialogues.
CoRR, 2015

Deconstructing the Ladder Network Architecture.
CoRR, 2015

A Controller Recognizer Framework: How necessary is recognition for control?
CoRR, 2015

EmoNets: Multimodal deep learning approaches for emotion recognition in video.
CoRR, 2015

Brain Tumor Segmentation with Deep Neural Networks.
CoRR, 2015

A Recurrent Latent Variable Model for Sequential Data.
CoRR, 2015

Describing Multimedia Content using Attention-based Encoder-Decoder Networks.
CoRR, 2015

Delving Deeper into Convolutional Networks for Learning Video Representations.
CoRR, 2015

Task Loss Estimation for Sequence Prediction.
CoRR, 2015

Dynamic Capacity Networks.
CoRR, 2015

Variance Reduction in SGD by Distributed Importance Sampling.
CoRR, 2015

Learning Distributed Representations from Reviews for Collaborative Filtering.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015

A Recurrent Latent Variable Model for Sequential Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Describing Videos by Exploiting Temporal Structure.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Generative Adversarial Networks.
CoRR, 2014

Deep Tempering.
CoRR, 2014

Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the Challenges of Physical Implementations of RBMs.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Deep Learning of Representations.
Proceedings of the Handbook on Neural Information Processing, 2013

Evaluating and Extending Trajectory Features for Activity Recognition.
Proceedings of the Advanced Topics in Computer Vision, 2013

Scaling Up Spike-and-Slab Models for Unsupervised Feature Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Representation Learning: A Review and New Perspectives.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Maxout Networks
CoRR, 2013

Joint Training Deep Boltzmann Machines for Classification
CoRR, 2013

Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines
CoRR, 2013

An empirical analysis of dropout in piecewise linear networks.
CoRR, 2013

An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks.
CoRR, 2013

Challenges in Representation Learning: A report on three machine learning contests.
CoRR, 2013

On the Challenges of Physical Implementations of RBMs.
CoRR, 2013

Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.
CoRR, 2013

Multi-Prediction Deep Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013


Maxout Networks.
Proceedings of the 30th International Conference on Machine Learning, 2013


Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.
Proceedings of the Unsupervised and Transfer Learning, 2012

Joint Training of Deep Boltzmann Machines
CoRR, 2012

Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions
CoRR, 2012

Disentangling Factors of Variation via Generative Entangling
CoRR, 2012

Efficient EM Training of Gaussian Mixtures with Missing Data
CoRR, 2012

Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives
CoRR, 2012

On Training Deep Boltzmann Machines
CoRR, 2012

Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery
CoRR, 2012

Large-Scale Feature Learning With Spike-and-Slab Sparse Coding.
Proceedings of the 29th International Conference on Machine Learning, 2012

Disentangling Factors of Variation for Facial Expression Recognition.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
A bistable computational model of recurring epileptiform activity as observed in rodent slice preparations.
Neural Networks, 2011

A Spike and Slab Restricted Boltzmann Machine.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All)
CoRR, 2011

On Tracking The Partition Function.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Unsupervised Models of Images by Spikeand-Slab RBMs.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Why Does Unsupervised Pre-training Help Deep Learning?
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Why Does Unsupervised Pre-training Help Deep Learning?
Journal of Machine Learning Research, 2010

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs
CoRR, 2010

2009
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
The rat as particle filter.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

An empirical evaluation of deep architectures on problems with many factors of variation.
Proceedings of the Machine Learning, 2007

2006
Representation and Timing in Theories of the Dopamine System.
Neural Computation, 2006

A Generative Model of Terrain for Autonomous Navigation in Vegetation.
I. J. Robotics Res., 2006

2005
Interacting Markov Random Fields for Simultaneous Terrain Modeling and Obstacle Detection.
Proceedings of the Robotics: Science and Systems I, 2005

2004
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Model Uncertainty in Classical Conditioning.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Timing and Partial Observability in the Dopamine System.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Modeling Temporal Structure in Classical Conditioning.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001


  Loading...