Courville, Aaron C.

59 publications

NeurIPS 2023 Double Gumbel Q-Learning David Yu-Tung Hui, Aaron C. Courville, Pierre-Luc Bacon

NeurIPS 2023 Group Robust Classification Without Any Group Information Christos Tsirigotis, Joao Monteiro, Pau Rodriguez, David Vazquez, Aaron C. Courville

NeurIPS 2023 Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron C. Courville

NeurIPS 2023 Language Model Alignment with Elastic Reset Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville

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 Versatile Energy-Based Probabilistic Models for High Energy Physics Taoli Cheng, Aaron C. Courville

NeurIPS 2022 Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare

NeurIPS 2022 Riemannian Diffusion Models Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville

NeurIPS 2021 A Variational Perspective on Diffusion-Based Generative Models and Score Matching Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville

NeurIPS 2021 Deep Reinforcement Learning at the Edge of the Statistical Precipice Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare

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

NeurIPS 2021 Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron C. Courville

AAAI 2020 Detecting Semantic Anomalies Faruk Ahmed, Aaron C. Courville

NeurIPS 2020 Unsupervised Learning of Dense Visual Representations Pedro O O. Pinheiro, Amjad Almahairi, Ryan Benmalek, Florian Golemo, Aaron C. Courville

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 No-Press Diplomacy: Modeling Multi-Agent Gameplay Philip Paquette, Yuchen Lu, Seton Steven Bocco, Max Smith, Satya O.-G., Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville

NeurIPS 2019 Ordered Memory Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville

AAAI 2018 FiLM: Visual Reasoning with a General Conditioning Layer Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, Aaron C. Courville

NeurIPS 2018 Improving Explorability in Variational Inference with Annealed Variational Objectives Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville

CoRL 2018 Sim-to-Real Transfer with Neural-Augmented Robot Simulation Florian Golemo, Adrien Ali Taïga, Aaron C. Courville, Pierre-Yves Oudeyer

NeurIPS 2018 Towards Text Generation with Adversarially Learned Neural Outlines Sandeep Subramanian, Sai Rajeswar Mudumba, Alessandro Sordoni, Adam Trischler, Aaron C. Courville, Chris Pal

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

ICLR 2017 Adversarially Learned Inference Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville

ICLR 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 2017 Calibrating Energy-Based Generative Adversarial Networks Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville

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

ICLR 2017 Deep Nets Don't Learn via Memorization David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville

IJCAI 2017 End-to-End Optimization of Goal-Driven and Visually Grounded Dialogue Systems Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin

ICLR 2017 Generalizable Features from Unsupervised Learning Mehdi Mirza, Aaron C. Courville, Yoshua Bengio

NeurIPS 2017 GibbsNet: Iterative Adversarial Inference for Deep Graphical Models Alex M Lamb, Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio

NeurIPS 2017 Improved Training of Wasserstein GANs Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, Aaron C. Courville

NeurIPS 2017 Modulating Early Visual Processing by Language Harm de Vries, Florian Strub, Jeremie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville

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

ICLR 2017 PixelVAE: A Latent Variable Model for Natural Images Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville

ICLR 2017 Recurrent Batch Normalization Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville

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

AAAI 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

ICLR 2016 Delving Deeper into Convolutional Networks for Learning Video Representations Nicolas Ballas, Li Yao, Chris Pal, Aaron C. Courville

NeurIPS 2016 Professor Forcing: A New Algorithm for Training Recurrent Networks Alex M Lamb, Anirudh Goyal ALIAS PARTH Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio

CVPRW 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

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

ICLR 2014 An Empirical Analysis of Dropout in Piecewise Linear Networks David Warde-Farley, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio

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

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

ICLR 2013 Joint Training Deep Boltzmann Machines for Classification Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio

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

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

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

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

NeurIPS 2011 On Tracking the Partition Function Guillaume Desjardins, Yoshua Bengio, Aaron C. Courville

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

NeurIPS 2009 An Infinite Factor Model Hierarchy via a Noisy-or Mechanism Douglas Eck, Yoshua Bengio, Aaron C. Courville

ICML 2007 An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio

NeurIPS 2007 The Rat as Particle Filter Aaron C. Courville, Nathaniel D. Daw

NeurIPS 2004 Similarity and Discrimination in Classical Conditioning: A Latent Variable Account Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky

NeurIPS 2003 Model Uncertainty in Classical Conditioning Aaron C. Courville, Geoffrey J. Gordon, David S. Touretzky, Nathaniel D. Daw

NeurIPS 2002 Timing and Partial Observability in the Dopamine System Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky

NeurIPS 2001 Modeling Temporal Structure in Classical Conditioning Aaron C. Courville, David S. Touretzky