Aaron C. Courville

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 282

Top Venues

CoRR

ICLR

ICML

NeurIPS

Publications

Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron C. Courville, Alessandro Sordoni, Rishabh Agarwal
V-STaR: Training Verifiers for Self-Taught Reasoners. CoRR (2024)
Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville
Language Model Alignment with Elastic Reset. NeurIPS (2023)
David Yu-Tung Hui, Aaron C. Courville, Pierre-Luc Bacon
Double Gumbel Q-Learning. NeurIPS (2023)
Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G. Bellemare, Aaron C. Courville
Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier. ICLR (2023)
Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. ICML (2023)
Yi Ren, Samuel Lavoie, Mikhail Galkin, Danica J. Sutherland, Aaron C. Courville
Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings. CoRR (2023)
Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan
Sparse Universal Transformer. CoRR (2023)
Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron C. Courville
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings. NeurIPS (2023)
Max Schwarzer, Jesse Farebrother, Joshua Greaves, Ekin Dogus Cubuk, Rishabh Agarwal, Aaron C. Courville, Marc G. Bellemare, Sergei V. Kalinin, Igor Mordatch, Pablo Samuel Castro, Kevin M. Roccapriore
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR (2023)
Dinghuai Zhang, Ricky Tian Qi Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. CoRR (2023)
Kyle Kastner, Tim Cooijmans, Yusong Wu, Aaron C. Courville
SUNMASK: Mask Enhanced Control in Step Unrolled Denoising Autoencoders. EvoMUSART@EvoStar (2023)
Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville
Language Model Alignment with Elastic Reset. CoRR (2023)
Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan
Sparse Universal Transformer. EMNLP (2023)
Taoli Cheng, Aaron C. Courville
Versatile Energy-Based Models for High Energy Physics. CoRR (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS (2023)
Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR (2023)
Tim Cooijmans, Milad Aghajohari, Aaron C. Courville
Meta-Value Learning: a General Framework for Learning with Learning Awareness. CoRR (2023)
Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR (2023)
Taoli Cheng, Aaron C. Courville
Versatile Energy-Based Probabilistic Models for High Energy Physics. NeurIPS (2023)
Adrien Ali Taïga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. ICLR (2023)
Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio
Distributional GFlowNets with Quantile Flows. CoRR (2023)
Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio
Generative Augmented Flow Networks. ICLR (2023)
Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron C. Courville
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. ICLR (2023)
Max Schwarzer, Johan Samir Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML (2023)
Christos Tsirigotis, João Monteiro, Pau Rodríguez, David Vázquez, Aaron C. Courville
Group Robust Classification Without Any Group Information. NeurIPS (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR (2023)
Christos Tsirigotis, João Monteiro, Pau Rodríguez, David Vázquez, Aaron C. Courville
Group Robust Classification Without Any Group Information. CoRR (2023)
Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron C. Courville
Unsupervised Dependency Graph Network. ACL (1) (2022)
Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
Fortuitous Forgetting in Connectionist Networks. CoRR (2022)
Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning. CoRR (2022)
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
The Primacy Bias in Deep Reinforcement Learning. ICML (2022)
Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
Teaching Algorithmic Reasoning via In-context Learning. CoRR (2022)
Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala
Building Robust Ensembles via Margin Boosting. CoRR (2022)
Rim Assouel, Lluís Castrejón, Aaron C. Courville, Nicolas Ballas, Yoshua Bengio
VIM: Variational Independent Modules for Video Prediction. CLeaR (2022)
Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. CoRR (2022)
Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron C. Courville
Riemannian Diffusion Models. CoRR (2022)
Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling. ICLR (2022)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress. NeurIPS (2022)
Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
Fortuitous Forgetting in Connectionist Networks. ICLR (2022)
Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
Generative Flow Networks for Discrete Probabilistic Modeling. ICML (2022)
Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
Cascaded Video Generation for Videos In-the-Wild. CoRR (2022)
Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala
Building Robust Ensembles via Margin Boosting. ICML (2022)
Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville
Unifying Likelihood-free Inference with Black-box Optimization and Beyond. ICLR (2022)
Sai Rajeswar, Pau Rodríguez, Soumye Singhal, David Vázquez, Aaron C. Courville
Multi-label Iterated Learning for Image Classification with Label Ambiguity. CVPR (2022)
Taoli Cheng, Aaron C. Courville
Invariant Representation Driven Neural Classifier for Anti-QCD Jet Tagging. CoRR (2022)
Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. ICLR (2022)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Beyond Tabula Rasa: Reincarnating Reinforcement Learning. CoRR (2022)
Kyle Kastner, Aaron C. Courville
R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS. CoRR (2022)
Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Kenji Kawaguchi, Ankit Vani, Aaron C. Courville
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. CoRR (2022)
Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
Cascaded Video Generation for Videos In-the-Wild. ICPR (2022)
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
The Primacy Bias in Deep Reinforcement Learning. CoRR (2022)
Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR (2022)
Arian Hosseini, Ankit Vani, Dzmitry Bahdanau, Alessandro Sordoni, Aaron C. Courville
On the Compositional Generalization Gap of In-Context Learning. BlackboxNLP@EMNLP (2022)
Sai Rajeswar, Issam Hadj Laradji, Pau Rodríguez, David Vázquez, Aaron C. Courville
Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation. BMVC (2022)
Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville
Learning to Dequantise with Truncated Flows. ICLR (2022)
Arian Hosseini, Ankit Vani, Dzmitry Bahdanau, Alessandro Sordoni, Aaron C. Courville
On the Compositional Generalization Gap of In-Context Learning. CoRR (2022)
Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
Generative Flow Networks for Discrete Probabilistic Modeling. CoRR (2022)
Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville
Riemannian Diffusion Models. NeurIPS (2022)
Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio
Chunked Autoregressive GAN for Conditional Waveform Synthesis. ICLR (2022)
Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio
Generative Augmented Flow Networks. CoRR (2022)
Sai Rajeswar, Pau Rodríguez, Soumye Singhal, David Vázquez, Aaron C. Courville
Multi-label Iterated Learning for Image Classification with Label Ambiguity. CoRR (2021)
Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville
A Variational Perspective on Diffusion-Based Generative Models and Score Matching. NeurIPS (2021)
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML (2021)
Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS (2021)
Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
Generative Compositional Augmentations for Scene Graph Prediction. ICCV (2021)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Deep Reinforcement Learning at the Edge of the Statistical Precipice. CoRR (2021)
David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville
Out-of-Distribution Generalization via Risk Extrapolation (REx). ICML (2021)
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan
Learning Task Decomposition with Ordered Memory Policy Network. ICLR (2021)
Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling. CoRR (2021)
Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
Hierarchical Video Generation for Complex Data. CoRR (2021)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Deep Reinforcement Learning at the Edge of the Statistical Precipice. NeurIPS (2021)
Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron C. Courville
Emergent Communication under Competition. AAMAS (2021)
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
Continuous Coordination As a Realistic Scenario for Lifelong Learning. ICML (2021)
Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron C. Courville
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling. ACL/IJCNLP (1) (2021)
Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu
Neural Approximate Sufficient Statistics for Implicit Models. ICLR (2021)
Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron C. Courville
Integrating Categorical Semantics into Unsupervised Domain Translation. ICLR (2021)
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville
Understanding by Understanding Not: Modeling Negation in Language Models. CoRR (2021)
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
Iterated learning for emergent systematicity in VQA. CoRR (2021)
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR (2021)
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
Iterated learning for emergent systematicity in VQA. ICLR (2021)
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. ICLR (2021)
Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio
Chunked Autoregressive GAN for Conditional Waveform Synthesis. CoRR (2021)
Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. CoRR (2021)
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR (2021)
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville
Understanding by Understanding Not: Modeling Negation in Language Models. NAACL-HLT (2021)
Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville
A Variational Perspective on Diffusion-Based Generative Models and Score Matching. CoRR (2021)
Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle. NAACL-HLT (2021)
Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron C. Courville
Emergent Communication under Competition. CoRR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS (2021)
Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville
Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond. CoRR (2021)
Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vázquez, Aaron C. Courville, Pedro O. Pinheiro
Haptics-based Curiosity for Sparse-reward Tasks. CoRL (2021)
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
Continuous Coordination As a Realistic Scenario for Lifelong Learning. CoRR (2021)
Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vázquez, Aaron C. Courville, Pedro O. Pinheiro
Touch-based Curiosity for Sparse-Reward Tasks. CoRR (2021)
Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron C. Courville
Systematic generalisation with group invariant predictions. ICLR (2021)
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
On Bonus-Based Exploration Methods in the Arcade Learning Environment. CoRR (2021)
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan
Learning Task Decomposition with Ordered Memory Policy Network. CoRR (2021)
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
Countering Language Drift with Seeded Iterated Learning. CoRR (2020)
Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell
Recursive Top-Down Production for Sentence Generation with Latent Trees. EMNLP (Findings) (2020)
Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron C. Courville
Integrating Categorical Semantics into Unsupervised Domain Translation. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aaron C. Courville