Aaron C. Courville

402 papers A* 95A 13B 3Misc 3Journal 228Unranked 57

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Stable Deep Reinforcement Learning via Isotropic Gaussian Representations. CoRR Ali Saheb Pasand, Johan S. Obando-Ceron, Aaron C. Courville, Pouya Bashivan, Pablo Samuel Castro
2026	J	`jnl`	Towards Sustainable Investment Policies Informed by Opponent Shaping. CoRR Juan Agustin Duque, Razvan Ciuca, Ayoub Echchahed, Hugo Larochelle, Aaron C. Courville
2025	J	`jnl`	A Comedy of Estimators: On KL Regularization in RL Training of LLMs. CoRR Vedant Shah, Johan S. Obando-Ceron, Vineet Jain, Brian R. Bartoldson, Bhavya Kailkhura, Sarthak Mittal, Glen Berseth, Pablo Samuel Castro, Yoshua Bengio, Nikolay Malkin, Moksh Jain, Siddarth Venkatraman, Aaron C. Courville
2025	J	`jnl`	Adaptive Accompaniment with ReaLchords. CoRR Yusong Wu, Tim Cooijmans, Kyle Kastner, Adam Roberts, Ian Simon, Alexander Scarlatos, Chris Donahue, Cassie Tarakajian, Shayegan Omidshafiei, Aaron C. Courville, Pablo Samuel Castro, Natasha Jaques, Cheng-Zhi Anna Huang
2025	J	`jnl`	Adaptive Computation Pruning for the Forgetting Transformer. CoRR Zhixuan Lin, Johan S. Obando-Ceron, Xu Owen He, Aaron C. Courville
2025	A*	`conf`	Advantage Alignment Algorithms. ICLR Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, Razvan Ciuca, Tianyu Zhang, Gauthier Gidel, Aaron C. Courville
2025	J	`jnl`	Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Han Lu, Yancheng He, Weixun Wang, Wenbo Su, Bo Zheng, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models. ICLR Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron C. Courville
2025	J	`jnl`	BiXSE: Improving Dense Retrieval via Probabilistic Graded Relevance Distillation. CoRR Christos Tsirigotis, Vaibhav Adlakha, João Monteiro, Aaron C. Courville, Perouz Taslakian
2025	J	`jnl`	Bias Analysis in Unconditional Image Generative Models. CoRR Xiaofeng Zhang, Michelle P. Lin, Simon Lacoste-Julien, Aaron C. Courville, Yash Goyal
2025	J	`jnl`	Compositional Discrete Latent Code for High Fidelity, Productive Diffusion Models. CoRR Samuel Lavoie, Michael Noukhovitch, Aaron C. Courville
2025	A*	`conf`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. ICLR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2025	J	`jnl`	Evolution Strategies at the Hyperscale. CoRR Bidipta Sarkar, Mattie Fellows, Juan Agustin Duque, Alistair Letcher, Antonio León Villares, Anya Sims, Dylan Cope, Jarek Liesen, Lukas Seier, Theo Wolf, Uljad Berdica, Alexander David Goldie, Aaron C. Courville, Karin Sevegnani, Shimon Whiteson, Jakob Nicolaus Foerster
2025	A*	`conf`	FLAM: Frame-Wise Language-Audio Modeling. ICML Yusong Wu, Christos Tsirigotis, Ke Chen, Cheng-Zhi Anna Huang, Aaron C. Courville, Oriol Nieto, Prem Seetharaman, Justin Salamon
2025	J	`jnl`	FLAM: Frame-Wise Language-Audio Modeling. CoRR Yusong Wu, Christos Tsirigotis, Ke Chen, Cheng-Zhi Anna Huang, Aaron C. Courville, Oriol Nieto, Prem Seetharaman, Justin Salamon
2025	A*	`conf`	Forgetting Transformer: Softmax Attention with a Forget Gate. ICLR Zhixuan Lin, Evgenii Nikishin, Xu Owen He, Aaron C. Courville
2025	J	`jnl`	Forgetting Transformer: Softmax Attention with a Forget Gate. CoRR Zhixuan Lin, Evgenii Nikishin, Xu Owen He, Aaron C. Courville
2025	J	`jnl`	Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction. CoRR Yusong Wu, Stephen Brade, Teng Ma, Tia-Jane Fowler, Enning Yang, Berker Banar, Aaron C. Courville, Natasha Jaques, Cheng-Zhi Anna Huang
2025	J	`jnl`	Learning Robust Social Strategies with Large Language Models. CoRR Dereck Piche, Mohammed Muqeeth, Milad Aghajohari, Juan Agustin Duque, Michael Noukhovitch, Aaron C. Courville
2025	J	`jnl`	Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning. CoRR Jiashun Liu, Zihao Wu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. ICML Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth
2025	J	`jnl`	Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. CoRR Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth
2025	J	`jnl`	Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation. CoRR Sangmin Bae, Yujin Kim, Reza Bayat, Sungnyun Kim, Jiyoun Ha, Tal Schuster, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Aaron C. Courville, Se-Young Yun
2025	A*	`conf`	Neuroplastic Expansion in Deep Reinforcement Learning. ICLR Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan
2025	J	`jnl`	Sample, Predict, then Proceed: Self-Verification Sampling for Tool Use of LLMs. CoRR Shangmin Guo, Omar Darwiche Domingues, Raphaël Avalos, Aaron C. Courville, Florian Strub
2025	A*	`conf`	Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study. ICLR Shawn Tan, Songlin Yang, Aaron C. Courville, Rameswar Panda, Yikang Shen
2025	J	`jnl`	Shape of Thought: When Distribution Matters More than Correctness in Reasoning Tasks. CoRR Abhranil Chandra, Ayush Agrawal, Arian Hosseini, Sebastian Fischmeister, Rishabh Agarwal, Navin Goyal, Aaron C. Courville
2025	J	`jnl`	Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents. CoRR Johan S. Obando-Ceron, Walter Mayor, Samuel Lavoie, Scott Fujimoto, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning. CoRR Roger Creus Castanyer, Johan S. Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	Streaming Generation for Music Accompaniment. CoRR Yusong Wu, Mason Wang, Heidi Lei, Stephen Brade, Lancelot Blanchard, Shih-Lun Wu, Aaron C. Courville, Cheng-Zhi Anna Huang
2025	A*	`conf`	The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. ICML Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	J	`jnl`	The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. ICML Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. CoRR Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	The Intricate Dance of Prompt Complexity, Quality, Diversity, and Consistency in T2I Models. CoRR Xiaofeng Zhang, Aaron C. Courville, Michal Drozdzal, Adriana Romero-Soriano
2025	J	`jnl`	The Markovian Thinker. CoRR Milad Aghajohari, Kamran Chitsaz, Amirhossein Kazemnejad, Sarath Chandar, Alessandro Sordoni, Aaron C. Courville, Siva Reddy
2025	A*	`conf`	VinePPO: Refining Credit Assignment in RL Training of LLMs. ICML Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron C. Courville, Nicolas Le Roux
2024	A*	`conf`	Adaptive Accompaniment with ReaLchords. ICML Yusong Wu, Tim Cooijmans, Kyle Kastner, Adam Roberts, Ian Simon, Alexander Scarlatos, Chris Donahue, Cassie Tarakajian, Shayegan Omidshafiei, Aaron C. Courville, Pablo Samuel Castro, Natasha Jaques, Cheng-Zhi Anna Huang
2024	J	`jnl`	Advantage Alignment Algorithms. CoRR Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, Tianyu Zhang, Aaron C. Courville
2024	J	`jnl`	Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models. CoRR Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron C. Courville
2024	J	`jnl`	Best Response Shaping. RLJ Milad Aghajohari, Tim Cooijmans, Juan Agustin Duque, Shunichi Akatsuka, Aaron C. Courville
2024	J	`jnl`	Best Response Shaping. CoRR Milad Aghajohari, Tim Cooijmans, Juan Agustin Duque, Shunichi Akatsuka, Aaron C. Courville
2024	A*	`conf`	Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. ICLR Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio
2024	J	`jnl`	Distributional GFlowNets with Quantile Flows. Trans. Mach. Learn. Res. Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio
2024	J	`jnl`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. CoRR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2024	A*	`conf`	GenRL: Multimodal-foundation world models for generalization in embodied agents. NeurIPS Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar Mudumba
2024	J	`jnl`	In deep reinforcement learning, a pruned network is a good network. CoRR Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2024	A*	`conf`	In value-based deep reinforcement learning, a pruned network is a good network. ICML Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2024	A*	`conf`	LOQA: Learning with Opponent Q-Learning Awareness. ICLR Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron C. Courville
2024	J	`jnl`	LOQA: Learning with Opponent Q-Learning Awareness. CoRR Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron C. Courville
2024	J	`jnl`	Managing multiple agents by automatically adjusting incentives. CoRR Shunichi Akatsuka, Yaemi Teramoto, Aaron C. Courville
2024	A*	`conf`	Modeling Caption Diversity in Contrastive Vision-Language Pretraining. ICML Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas
2024	J	`jnl`	Modeling Caption Diversity in Contrastive Vision-Language Pretraining. CoRR Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas
2024	J	`jnl`	Multimodal foundation world models for generalist embodied agents. CoRR Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar
2024	J	`jnl`	Neuroplastic Expansion in Deep Reinforcement Learning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan
2024	J	`jnl`	Not All LLM Reasoners Are Created Equal. CoRR Arian Hosseini, Alessandro Sordoni, Daniel Toyama, Aaron C. Courville, Rishabh Agarwal
2024	J	`jnl`	On the consistency of hyper-parameter selection in value-based deep reinforcement learning. RLJ Johan S. Obando-Ceron, João Guilherme Madeira Araújo, Aaron C. Courville, Pablo Samuel Castro
2024	J	`jnl`	On the consistency of hyper-parameter selection in value-based deep reinforcement learning. CoRR Johan S. Obando-Ceron, João G. M. Araújo, Aaron C. Courville, Pablo Samuel Castro
2024	—	`conf`	SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning. ECCV (69) Bac Nguyen, Stefan Uhlich, Fabien Cardinaux, Lukas Mauch, Marzieh Edraki, Aaron C. Courville
2024	J	`jnl`	SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning. CoRR Bac Nguyen, Stefan Uhlich, Fabien Cardinaux, Lukas Mauch, Marzieh Edraki, Aaron C. Courville
2024	—	`conf`	SPARO: Selective Attention for Robust and Compositional Transformer Encodings for Vision. ECCV (66) Ankit Vani, Bac Nguyen, Samuel Lavoie, Ranjay Krishna, Aaron C. Courville
2024	J	`jnl`	SPARO: Selective Attention for Robust and Compositional Transformer Encodings for Vision. CoRR Ankit Vani, Bac Nguyen, Samuel Lavoie, Ranjay Krishna, Aaron C. Courville
2024	J	`jnl`	Scattered Mixture-of-Experts Implementation. CoRR Shawn Tan, Yikang Shen, Rameswar Panda, Aaron C. Courville
2024	J	`jnl`	Stick-breaking Attention. CoRR Shawn Tan, Yikang Shen, Songlin Yang, Aaron C. Courville, Rameswar Panda
2024	A*	`conf`	The Curse of Diversity in Ensemble-Based Exploration. ICLR Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin, Aaron C. Courville
2024	J	`jnl`	The Curse of Diversity in Ensemble-Based Exploration. CoRR Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin, Aaron C. Courville
2024	J	`jnl`	V-STaR: Training Verifiers for Self-Taught Reasoners. CoRR Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron C. Courville, Alessandro Sordoni, Rishabh Agarwal
2024	J	`jnl`	VinePPO: Unlocking RL Potential For LLM Reasoning Through Refined Credit Assignment. CoRR Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron C. Courville, Nicolas Le Roux
2023	A*	`conf`	Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
2023	J	`jnl`	Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
2023	J	`jnl`	Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. CoRR Dinghuai Zhang, Ricky Tian Qi Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio
2023	J	`jnl`	Distributional GFlowNets with Quantile Flows. CoRR Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio
2023	A*	`conf`	Double Gumbel Q-Learning. NeurIPS David Yu-Tung Hui, Aaron C. Courville, Pierre-Luc Bacon
2023	A*	`conf`	Generative Augmented Flow Networks. ICLR Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio
2023	A*	`conf`	Group Robust Classification Without Any Group Information. NeurIPS Christos Tsirigotis, João Monteiro, Pau Rodríguez, David Vázquez, Aaron C. Courville
2023	J	`jnl`	Group Robust Classification Without Any Group Information. CoRR Christos Tsirigotis, João Monteiro, Pau Rodríguez, David Vázquez, Aaron C. Courville
2023	J	`jnl`	Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings. CoRR Yi Ren, Samuel Lavoie, Mikhail Galkin, Danica J. Sutherland, Aaron C. Courville
2023	A*	`conf`	Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings. NeurIPS Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron C. Courville
2023	A*	`conf`	Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. ICLR Adrien Ali Taïga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare
2023	A*	`conf`	Language Model Alignment with Elastic Reset. NeurIPS Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville
2023	J	`jnl`	Language Model Alignment with Elastic Reset. CoRR Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville
2023	A*	`conf`	Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
2023	J	`jnl`	Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR 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
2023	J	`jnl`	Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	A*	`conf`	Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	A*	`conf`	Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. ICML Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
2023	J	`jnl`	Meta-Value Learning: a General Framework for Learning with Learning Awareness. CoRR Tim Cooijmans, Milad Aghajohari, Aaron C. Courville
2023	—	`conf`	SUNMASK: Mask Enhanced Control in Step Unrolled Denoising Autoencoders. EvoMUSART@EvoStar Kyle Kastner, Tim Cooijmans, Yusong Wu, Aaron C. Courville
2023	A*	`conf`	Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier. ICLR Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G. Bellemare, Aaron C. Courville
2023	A*	`conf`	Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. ICLR Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron C. Courville
2023	A*	`conf`	Sparse Universal Transformer. EMNLP Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan
2023	J	`jnl`	Sparse Universal Transformer. CoRR Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan
2023	J	`jnl`	Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods. Trans. Mach. Learn. Res. Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni
2023	J	`jnl`	Versatile Energy-Based Models for High Energy Physics. CoRR Taoli Cheng, Aaron C. Courville
2023	A*	`conf`	Versatile Energy-Based Probabilistic Models for High Energy Physics. NeurIPS Taoli Cheng, Aaron C. Courville
2022	J	`jnl`	Beyond Tabula Rasa: Reincarnating Reinforcement Learning. CoRR Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
2022	A*	`conf`	Building Robust Ensembles via Margin Boosting. ICML Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala
2022	J	`jnl`	Building Robust Ensembles via Margin Boosting. CoRR Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala
2022	B	`conf`	Cascaded Video Generation for Videos In-the-Wild. ICPR Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
2022	J	`jnl`	Cascaded Video Generation for Videos In-the-Wild. CoRR Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
2022	A*	`conf`	Chunked Autoregressive GAN for Conditional Waveform Synthesis. ICLR Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio
2022	A	`conf`	Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation. BMVC Sai Rajeswar, Issam Hadj Laradji, Pau Rodríguez, David Vázquez, Aaron C. Courville
2022	A*	`conf`	DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. ICLR Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
2022	J	`jnl`	Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning. CoRR Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni
2022	A*	`conf`	Fortuitous Forgetting in Connectionist Networks. ICLR Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
2022	J	`jnl`	Fortuitous Forgetting in Connectionist Networks. CoRR Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
2022	J	`jnl`	Generative Augmented Flow Networks. CoRR Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio
2022	A*	`conf`	Generative Flow Networks for Discrete Probabilistic Modeling. ICML Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
2022	J	`jnl`	Generative Flow Networks for Discrete Probabilistic Modeling. CoRR Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
2022	J	`jnl`	Invariant Representation Driven Neural Classifier for Anti-QCD Jet Tagging. CoRR Taoli Cheng, Aaron C. Courville
2022	J	`jnl`	Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
2022	A*	`conf`	Learning to Dequantise with Truncated Flows. ICLR Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville
2022	A*	`conf`	MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling. ICLR Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel
2022	A*	`conf`	Multi-label Iterated Learning for Image Classification with Label Ambiguity. CVPR Sai Rajeswar, Pau Rodríguez, Soumye Singhal, David Vázquez, Aaron C. Courville
2022	—	`conf`	On the Compositional Generalization Gap of In-Context Learning. BlackboxNLP@EMNLP Arian Hosseini, Ankit Vani, Dzmitry Bahdanau, Alessandro Sordoni, Aaron C. Courville
2022	J	`jnl`	On the Compositional Generalization Gap of In-Context Learning. CoRR Arian Hosseini, Ankit Vani, Dzmitry Bahdanau, Alessandro Sordoni, Aaron C. Courville
2022	J	`jnl`	R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS. CoRR Kyle Kastner, Aaron C. Courville
2022	A*	`conf`	Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress. NeurIPS Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
2022	A*	`conf`	Riemannian Diffusion Models. NeurIPS Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville
2022	J	`jnl`	Riemannian Diffusion Models. CoRR Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron C. Courville
2022	J	`jnl`	Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. CoRR Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Kenji Kawaguchi, Ankit Vani, Aaron C. Courville
2022	J	`jnl`	Teaching Algorithmic Reasoning via In-context Learning. CoRR Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
2022	A*	`conf`	The Primacy Bias in Deep Reinforcement Learning. ICML Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
2022	J	`jnl`	The Primacy Bias in Deep Reinforcement Learning. CoRR Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
2022	A*	`conf`	Unifying Likelihood-free Inference with Black-box Optimization and Beyond. ICLR Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville
2022	—	`conf`	Unsupervised Dependency Graph Network. ACL (1) Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron C. Courville
2022	J	`jnl`	Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. CoRR Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
2022	—	`conf`	VIM: Variational Independent Modules for Video Prediction. CLeaR Rim Assouel, Lluís Castrejón, Aaron C. Courville, Nicolas Ballas, Yoshua Bengio
2021	A*	`conf`	A Variational Perspective on Diffusion-Based Generative Models and Score Matching. NeurIPS Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville
2021	J	`jnl`	A Variational Perspective on Diffusion-Based Generative Models and Score Matching. CoRR Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville
2021	A*	`conf`	Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
2021	J	`jnl`	Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
2021	J	`jnl`	Chunked Autoregressive GAN for Conditional Waveform Synthesis. CoRR Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio
2021	A*	`conf`	Continuous Coordination As a Realistic Scenario for Lifelong Learning. ICML Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
2021	J	`jnl`	Continuous Coordination As a Realistic Scenario for Lifelong Learning. CoRR Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
2021	A*	`conf`	Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. ICLR Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville
2021	J	`jnl`	DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. CoRR Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine
2021	A*	`conf`	Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
2021	A*	`conf`	Deep Reinforcement Learning at the Edge of the Statistical Precipice. NeurIPS Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
2021	J	`jnl`	Deep Reinforcement Learning at the Edge of the Statistical Precipice. CoRR Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
2021	A	`conf`	Emergent Communication under Competition. AAMAS Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron C. Courville
2021	J	`jnl`	Emergent Communication under Competition. CoRR Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron C. Courville
2021	—	`conf`	Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle. NAACL-HLT Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville
2021	A*	`conf`	Generative Compositional Augmentations for Scene Graph Prediction. ICCV Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
2021	A*	`conf`	Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
2021	Misc	`conf`	Haptics-based Curiosity for Sparse-reward Tasks. CoRL Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vázquez, Aaron C. Courville, Pedro O. Pinheiro
2021	J	`jnl`	Hierarchical Video Generation for Complex Data. CoRR Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
2021	A*	`conf`	Integrating Categorical Semantics into Unsupervised Domain Translation. ICLR Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron C. Courville
2021	A*	`conf`	Iterated learning for emergent systematicity in VQA. ICLR Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
2021	J	`jnl`	Iterated learning for emergent systematicity in VQA. CoRR Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
2021	A*	`conf`	Learning Task Decomposition with Ordered Memory Policy Network. ICLR Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan
2021	J	`jnl`	Learning Task Decomposition with Ordered Memory Policy Network. CoRR Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan
2021	J	`jnl`	MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling. CoRR Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel
2021	J	`jnl`	Multi-label Iterated Learning for Image Classification with Label Ambiguity. CoRR Sai Rajeswar, Pau Rodríguez, Soumye Singhal, David Vázquez, Aaron C. Courville
2021	A*	`conf`	Neural Approximate Sufficient Statistics for Implicit Models. ICLR Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu
2021	J	`jnl`	On Bonus-Based Exploration Methods in the Arcade Learning Environment. CoRR Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
2021	A*	`conf`	Out-of-Distribution Generalization via Risk Extrapolation (REx). ICML David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville
2021	A*	`conf`	Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2021	J	`jnl`	Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2021	—	`conf`	StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling. ACL/IJCNLP (1) Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron C. Courville
2021	A*	`conf`	Systematic generalisation with group invariant predictions. ICLR Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron C. Courville
2021	J	`jnl`	Touch-based Curiosity for Sparse-Reward Tasks. CoRR Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vázquez, Aaron C. Courville, Pedro O. Pinheiro
2021	—	`conf`	Understanding by Understanding Not: Modeling Negation in Language Models. NAACL-HLT Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville
2021	J	`jnl`	Understanding by Understanding Not: Modeling Negation in Language Models. CoRR Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville
2021	J	`jnl`	Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond. CoRR Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville
2020	—	`conf`	A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio
2020	J	`jnl`	A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio
2020	A*	`conf`	AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. ICML Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang
2020	J	`jnl`	AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. CoRR Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang
2020	J	`jnl`	Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models. CoRR Chin-Wei Huang, Laurent Dinh, Aaron C. Courville
2020	J	`jnl`	Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. CoRR Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville
2020	A*	`conf`	Countering Language Drift with Seeded Iterated Learning. ICML Yuchen Lu, Soumye Singhal, Florian Strub, Aaron C. Courville, Olivier Pietquin
2020	J	`jnl`	Countering Language Drift with Seeded Iterated Learning. CoRR Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
2020	J	`jnl`	Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
2020	A*	`conf`	Detecting Semantic Anomalies. AAAI Faruk Ahmed, Aaron C. Courville
2020	J	`jnl`	Explicitly Modeling Syntax in Language Model improves Generalization. CoRR Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville
2020	J	`jnl`	Generative Graph Perturbations for Scene Graph Prediction. CoRR Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
2020	J	`jnl`	Generative adversarial networks. Commun. ACM Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2020	J	`jnl`	Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
2020	A	`conf`	Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. BMVC Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
2020	J	`jnl`	Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. CoRR Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
2020	J	`jnl`	Integrating Categorical Semantics into Unsupervised Domain Translation. CoRR Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron C. Courville
2020	J	`jnl`	NU-GAN: High resolution neural upsampling with GAN. CoRR Rithesh Kumar, Kundan Kumar, Vicki Anand, Yoshua Bengio, Aaron C. Courville
2020	J	`jnl`	Neural Approximate Sufficient Statistics for Implicit Models. CoRR Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu
2020	A*	`conf`	On Bonus Based Exploration Methods In The Arcade Learning Environment. ICLR Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
2020	J	`jnl`	Out-of-Distribution Generalization via Risk Extrapolation (REx). CoRR David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Rémi Le Priol, Aaron C. Courville
2020	J	`jnl`	Pix2Shape - Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation. CoRR Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vázquez, Derek Nowrouzezahrai, Aaron C. Courville
2020	J	`jnl`	Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation. Int. J. Comput. Vis. Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vázquez, Derek Nowrouzezahrai, Aaron C. Courville
2020	—	`conf`	Recursive Top-Down Production for Sentence Generation with Latent Trees. EMNLP (Findings) Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell
2020	J	`jnl`	Recursive Top-Down Production for Sentence Generation with Latent Trees. CoRR Shawn Tan, Yikang Shen, Timothy J. O'Donnell, Alessandro Sordoni, Aaron C. Courville
2020	A	`conf`	Stochastic Neural Network with Kronecker Flow. AISTATS Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2020	J	`jnl`	StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling. CoRR Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron C. Courville
2020	—	`conf`	Supervised Seeded Iterated Learning for Interactive Language Learning. EMNLP (1) Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
2020	J	`jnl`	Supervised Seeded Iterated Learning for Interactive Language Learning. CoRR Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
2020	A*	`conf`	Unsupervised Learning of Dense Visual Representations. NeurIPS Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville
2020	J	`jnl`	Unsupervised Learning of Dense Visual Representations. CoRR Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville
2019	J	`jnl`	Adversarial Computation of Optimal Transport Maps. CoRR Jacob Leygonie, Jennifer She, Amjad Almahairi, Sai Rajeswar, Aaron C. Courville
2019	A*	`conf`	Batch Weight for Domain Adaptation With Mass Shift. ICCV Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville
2019	J	`jnl`	Batch weight for domain adaptation with mass shift. CoRR Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville
2019	J	`jnl`	Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment. CoRR Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
2019	—	`conf`	CLOSURE: Assessing Systematic Generalization of CLEVR Models. ViGIL@NeurIPS Harm de Vries, Dzmitry Bahdanau, Shikhar Murty, Aaron C. Courville, Philippe Beaudoin
2019	J	`jnl`	CLOSURE: Assessing Systematic Generalization of CLEVR Models. CoRR Dzmitry Bahdanau, Harm de Vries, Timothy J. O'Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, Aaron C. Courville
2019	J	`jnl`	Counterpoint by Convolution. CoRR Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron C. Courville, Douglas Eck
2019	A	`conf`	Deep Generative Modeling of LiDAR Data. IROS Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau
2019	J	`jnl`	Detecting semantic anomalies. CoRR Faruk Ahmed, Aaron C. Courville
2019	A*	`conf`	Hierarchical Importance Weighted Autoencoders. ICML Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	Hierarchical Importance Weighted Autoencoders. CoRR Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery. CoRR Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron C. Courville, Yoshua Bengio, Joseph Paul Cohen
2019	A*	`conf`	Improved Conditional VRNNs for Video Prediction. ICCV Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
2019	J	`jnl`	Improved Conditional VRNNs for Video Prediction. CoRR Lluís Castrejón, Nicolas Ballas, Aaron C. Courville
2019	J	`jnl`	Investigating Biases in Textual Entailment Datasets. CoRR Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville
2019	J	`jnl`	Maximum Entropy Generators for Energy-Based Models. CoRR Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio
2019	A*	`conf`	MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. NeurIPS Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville
2019	J	`jnl`	MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. CoRR Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville
2019	J	`jnl`	No Press Diplomacy: Modeling Multi-Agent Gameplay. CoRR Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron C. Courville
2019	A*	`conf`	No-Press Diplomacy: Modeling Multi-Agent Gameplay. NeurIPS Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville
2019	J	`jnl`	Note on the bias and variance of variational inference. CoRR Chin-Wei Huang, Aaron C. Courville
2019	A*	`conf`	On the Spectral Bias of Neural Networks. ICML Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
2019	A*	`conf`	Ordered Memory. NeurIPS Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville
2019	J	`jnl`	Ordered Memory. CoRR Yikang Shen, Shawn Tan, Seyedarian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville
2019	—	`conf`	Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. ICLR Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville
2019	A	`conf`	Probability Distillation: A Caveat and Alternatives. UAI Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville
2019	Misc	`conf`	Representation Mixing for TTS Synthesis. ICASSP Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville
2019	J	`jnl`	Selective Brain Damage: Measuring the Disparate Impact of Model Pruning. CoRR Sara Hooker, Aaron C. Courville, Yann N. Dauphin, Andrea Frome
2019	J	`jnl`	Stochastic Neural Network with Kronecker Flow. CoRR Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2019	—	`conf`	Systematic Generalization: What Is Required and Can It Be Learned? ICLR (Poster) Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries, Aaron C. Courville
2019	A	`conf`	VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. BMVC Catalina Cangea, Eugene Belilovsky, Aaron C. Courville
2019	—	`conf`	VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. ViGIL@NeurIPS Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville
2019	J	`jnl`	VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. CoRR Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville
2018	J	`jnl`	Approximate Exploration through State Abstraction. CoRR Adrien Ali Taïga, Aaron C. Courville, Marc G. Bellemare
2018	A*	`conf`	Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. ICML Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville
2018	J	`jnl`	Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. CoRR Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville
2018	J	`jnl`	Blindfold Baselines for Embodied QA. CoRR Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville
2018	J	`jnl`	Deep Generative Modeling of LiDAR Data. CoRR Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau
2018	A*	`conf`	FiLM: Visual Reasoning with a General Conditioning Layer. AAAI Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, Aaron C. Courville
2018	J	`jnl`	Generating Contradictory, Neutral, and Entailing Sentences. CoRR Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville
2018	J	`jnl`	Harmonic Recomposition using Conditional Autoregressive Modeling. CoRR Kyle Kastner, Rithesh Kumar, Tim Cooijmans, Aaron C. Courville
2018	J	`jnl`	Hierarchical Adversarially Learned Inference. CoRR Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron C. Courville
2018	—	`conf`	HoME: a Household Multimodal Environment. ICLR (Workshop) Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2018	A*	`conf`	Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville
2018	J	`jnl`	Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville
2018	J	`jnl`	Learning Distributed Representations from Reviews for Collaborative Filtering. CoRR Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville
2018	J	`jnl`	MINE: Mutual Information Neural Estimation. CoRR Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm, Aaron C. Courville
2018	J	`jnl`	Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. CoRR Vikas Verma, Alex Lamb, Christopher Beckham, Aaron C. Courville, Ioannis Mitliagkas, Yoshua Bengio
2018	A*	`conf`	Mutual Information Neural Estimation. ICML Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R. Devon Hjelm, Aaron C. Courville
2018	A*	`conf`	Neural Autoregressive Flows. ICML Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville
2018	J	`jnl`	Neural Autoregressive Flows. CoRR Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville
2018	—	`conf`	Neural Language Modeling by Jointly Learning Syntax and Lexicon. ICLR (Poster) Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville
2018	J	`jnl`	On the Learning Dynamics of Deep Neural Networks. CoRR Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron C. Courville, Yoshua Bengio
2018	J	`jnl`	On the Spectral Bias of Deep Neural Networks. CoRR Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
2018	J	`jnl`	Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. CoRR Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville
2018	J	`jnl`	Planning in Dynamic Environments with Conditional Autoregressive Models. CoRR Johanna Hansen, Kyle Kastner, Aaron C. Courville, Gregory Dudek
2018	J	`jnl`	Representation Mixing for TTS Synthesis. CoRR Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville
2018	Misc	`conf`	Sim-to-Real Transfer with Neural-Augmented Robot Simulation. CoRL Florian Golemo, Adrien Ali Taïga, Aaron C. Courville, Pierre-Yves Oudeyer
2018	—	`conf`	Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. ACL (1) Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio
2018	J	`jnl`	Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. CoRR Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio
2018	J	`jnl`	Systematic Generalization: What Is Required and Can It Be Learned? CoRR Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries, Aaron C. Courville
2018	A*	`conf`	Towards Text Generation with Adversarially Learned Neural Outlines. NeurIPS Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron C. Courville, Chris Pal
2018	—	`conf`	Visual Reasoning with Multi-hop Feature Modulation. ECCV (5) Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin
2018	J	`jnl`	Visual Reasoning with Multi-hop Feature Modulation. CoRR Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin
2017	A*	`conf`	A Closer Look at Memorization in Deep Networks. ICML Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien
2017	J	`jnl`	A Closer Look at Memorization in Deep Networks. CoRR Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien
2017	A*	`conf`	A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering. CVPR Tegan Maharaj, Nicolas Ballas, Anna Rohrbach, Aaron C. Courville, Christopher Joseph Pal
2017	A*	`conf`	A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. AAAI Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2017	—	`conf`	Adversarial Generation of Natural Language. Rep4NLP@ACL Sandeep Subramanian, Sai Rajeswar, Francis Dutil, Chris Pal, Aaron C. Courville
2017	J	`jnl`	Adversarial Generation of Natural Language. CoRR Sai Rajeswar, Sandeep Subramanian, Francis Dutil, Christopher Joseph Pal, Aaron C. Courville
2017	—	`conf`	Adversarially Learned Inference. ICLR (Poster) Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
2017	—	`conf`	An Actor-Critic Algorithm for Sequence Prediction. ICLR (Poster) Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2017	J	`jnl`	Bayesian Hypernetworks. CoRR David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville
2017	J	`jnl`	Brain tumor segmentation with Deep Neural Networks. Medical Image Anal. Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle
2017	—	`conf`	Calibrating Energy-based Generative Adversarial Networks. ICLR (Poster) Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville
2017	J	`jnl`	Calibrating Energy-based Generative Adversarial Networks. CoRR Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville
2017	—	`conf`	Char2Wav: End-to-End Speech Synthesis. ICLR (Workshop) Jose Sotelo, Soroush Mehri, Kundan Kumar, João Felipe Santos, Kyle Kastner, Aaron C. Courville, Yoshua Bengio
2017	—	`conf`	Counterpoint by Convolution. ISMIR Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron C. Courville, Douglas Eck
2017	—	`conf`	Deep Nets Don't Learn via Memorization. ICLR (Workshop) David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville
2017	A*	`conf`	End-to-end optimization of goal-driven and visually grounded dialogue systems. IJCAI Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin
2017	J	`jnl`	End-to-end optimization of goal-driven and visually grounded dialogue systems. CoRR Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin
2017	J	`jnl`	FiLM: Visual Reasoning with a General Conditioning Layer. CoRR Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, Aaron C. Courville
2017	—	`conf`	Generalizable Features From Unsupervised Learning. ICLR (Workshop) Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2017	—	`conf`	GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. NIPS Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
2017	J	`jnl`	GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. CoRR Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
2017	A*	`conf`	GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. CVPR Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
2017	J	`jnl`	HoME: a Household Multimodal Environment. CoRR Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2017	—	`conf`	Improved Training of Wasserstein GANs. NIPS Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville
2017	J	`jnl`	Improved Training of Wasserstein GANs. CoRR Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville
2017	J	`jnl`	Learnable Explicit Density for Continuous Latent Space and Variational Inference. CoRR Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron C. Courville
2017	J	`jnl`	Learning Visual Reasoning Without Strong Priors. CoRR Ethan Perez, Harm de Vries, Florian Strub, Vincent Dumoulin, Aaron C. Courville
2017	—	`conf`	Modulating early visual processing by language. NIPS Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
2017	J	`jnl`	Modulating early visual processing by language. CoRR Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
2017	J	`jnl`	Movie Description. Int. J. Comput. Vis. Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
2017	A*	`conf`	Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. AAAI Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville
2017	J	`jnl`	Neural Language Modeling by Jointly Learning Syntax and Lexicon. CoRR Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville
2017	A*	`conf`	Piecewise Latent Variables for Neural Variational Text Processing. EMNLP Iulian Vlad Serban, Alexander G. Ororbia II, Joelle Pineau, Aaron C. Courville
2017	—	`conf`	Piecewise Latent Variables for Neural Variational Text Processing. SPNLP@EMNLP Iulian Vlad Serban, Alexander Ororbia, Joelle Pineau, Aaron C. Courville
2017	—	`conf`	PixelVAE: A Latent Variable Model for Natural Images. ICLR (Poster) Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville
2017	—	`conf`	Recurrent Batch Normalization. ICLR (Poster) Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville
2017	—	`conf`	SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. ICLR (Poster) Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio
2017	J	`jnl`	Self-organized Hierarchical Softmax. CoRR Yikang Shen, Shawn Tan, Christopher Joseph Pal, Aaron C. Courville
2017	J	`jnl`	Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks. CoRR Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, César Laurent, Yoshua Bengio, Aaron C. Courville
2017	—	`conf`	Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal
2016	J	`jnl`	A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images. CoRR David Vázquez, Jorge Bernal, Francisco Javier Sánchez, Gloria Fernández-Esparrach, Antonio M. López, Adriana Romero, Michal Drozdzal, Aaron C. Courville
2016	J	`jnl`	A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. CoRR Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering. CoRR Tegan Maharaj, Nicolas Ballas, Aaron C. Courville, Christopher Joseph Pal
2016	J	`jnl`	Adversarially Learned Inference. CoRR Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
2016	J	`jnl`	An Actor-Critic Algorithm for Sequence Prediction. CoRR Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2016	A*	`conf`	Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models. AAAI Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau
2016	A*	`conf`	Deconstructing the Ladder Network Architecture. ICML Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio
2016	B	`conf`	Deep Learning Vector Quantization. ESANN Harm de Vries, Roland Memisevic, Aaron C. Courville
2016	—	`book`	Deep Learning. Ian J. Goodfellow, Yoshua Bengio, Aaron C. Courville
2016	A*	`conf`	Delving Deeper into Convolutional Networks for Learning Video Representations. ICLR (Poster) Nicolas Ballas, Li Yao, Chris Pal, Aaron C. Courville
2016	J	`jnl`	Discriminative Regularization for Generative Models. CoRR Alex Lamb, Vincent Dumoulin, Aaron C. Courville
2016	A*	`conf`	Dynamic Capacity Networks. ICML Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville
2016	J	`jnl`	EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 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, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio
2016	J	`jnl`	First Result on Arabic Neural Machine Translation. CoRR Amjad Almahairi, Kyunghyun Cho, Nizar Habash, Aaron C. Courville
2016	J	`jnl`	Generalizable Features From Unsupervised Learning. CoRR Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2016	—	`conf`	Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. ACL (1) Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. CoRR Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	GuessWhat?! Visual object discovery through multi-modal dialogue. CoRR Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
2016	J	`jnl`	Movie Description. CoRR Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
2016	J	`jnl`	Multi-modal Variational Encoder-Decoders. CoRR Iulian Vlad Serban, Alexander G. Ororbia II, Joelle Pineau, Aaron C. Courville
2016	J	`jnl`	Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. CoRR Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville
2016	J	`jnl`	PixelVAE: A Latent Variable Model for Natural Images. CoRR Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville
2016	—	`conf`	Professor Forcing: A New Algorithm for Training Recurrent Networks. NIPS Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Professor Forcing: A New Algorithm for Training Recurrent Networks. CoRR Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	—	`conf`	ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation. CVPR Workshops Francesco Visin, Adriana Romero, Kyunghyun Cho, Matteo Matteucci, Marco Ciccone, Kyle Kastner, Yoshua Bengio, Aaron C. Courville
2016	J	`jnl`	Recurrent Batch Normalization. CoRR Tim Cooijmans, Nicolas Ballas, César Laurent, Aaron C. Courville
2016	J	`jnl`	SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. CoRR Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR 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, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2016	A	`conf`	Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks. INTERSPEECH Ying Zhang, Mohammad Pezeshki, Philémon Brakel, Saizheng Zhang, César Laurent, Yoshua Bengio, Aaron C. Courville
2016	J	`jnl`	Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal
2015	J	`jnl`	A Controller Recognizer Framework: How necessary is recognition for control? CoRR Marcin Moczulski, Kelvin Xu, Aaron C. Courville, Kyunghyun Cho
2015	—	`conf`	A Recurrent Latent Variable Model for Sequential Data. NIPS Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	A Recurrent Latent Variable Model for Sequential Data. CoRR Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	Brain Tumor Segmentation with Deep Neural Networks. CoRR Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle
2015	J	`jnl`	Challenges in representation learning: A report on three machine learning contests. Neural Networks 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, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2015	J	`jnl`	Deconstructing the Ladder Network Architecture. CoRR Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks. IEEE Trans. Multim. Kyunghyun Cho, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	Describing Multimedia Content using Attention-based Encoder-Decoder Networks. CoRR Kyunghyun Cho, Aaron C. Courville, Yoshua Bengio
2015	A*	`conf`	Describing Videos by Exploiting Temporal Structure. ICCV Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	Dynamic Capacity Networks. CoRR Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher J. Pal, Yoshua Bengio
2015	J	`jnl`	Hierarchical Neural Network Generative Models for Movie Dialogues. CoRR Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau
2015	A	`conf`	Learning Distributed Representations from Reviews for Collaborative Filtering. RecSys Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville
2015	J	`jnl`	ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks. CoRR Francesco Visin, Kyle Kastner, Kyunghyun Cho, Matteo Matteucci, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	ReSeg: A Recurrent Neural Network for Object Segmentation. CoRR Francesco Visin, Kyle Kastner, Aaron C. Courville, Yoshua Bengio, Matteo Matteucci, Kyunghyun Cho
2015	A*	`conf`	Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. ICML Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio
2015	J	`jnl`	Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio
2015	J	`jnl`	Task Loss Estimation for Sequence Prediction. CoRR Dzmitry Bahdanau, Dmitriy Serdyuk, Philemon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research. CoRR Atousa Torabi, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	Variance Reduction in SGD by Distributed Importance Sampling. CoRR Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron C. Courville, Yoshua Bengio
2015	J	`jnl`	Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism. CoRR Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville
2014	—	`conf`	An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks. ICLR (Poster) Ian J. Goodfellow, Mehdi Mirza, Xia Da, Aaron C. Courville, Yoshua Bengio
2014	—	`conf`	An empirical analysis of dropout in piecewise linear networks. ICLR (Poster) David Warde-Farley, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2014	J	`jnl`	Deep Tempering. CoRR Guillaume Desjardins, Heng Luo, Aaron C. Courville, Yoshua Bengio
2014	—	`conf`	Generative Adversarial Nets. NIPS Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2014	J	`jnl`	Generative Adversarial Networks. CoRR Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2014	A*	`conf`	On the Challenges of Physical Implementations of RBMs. AAAI Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2014	J	`jnl`	The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. IEEE Trans. Pattern Anal. Mach. Intell. Aaron C. Courville, Guillaume Desjardins, James Bergstra, Yoshua Bengio
2013	—	`conf`	Challenges in Representation Learning: A Report on Three Machine Learning Contests. ICONIP (3) 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, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	J	`jnl`	Challenges in Representation Learning: A report on three machine learning contests. CoRR 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, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	B	`conf`	Combining modality specific deep neural networks for emotion recognition in video. ICMI 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, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu
2013	—	`ch.`	Deep Learning of Representations. Handbook on Neural Information Processing Yoshua Bengio, Aaron C. Courville
2013	J	`jnl`	Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation. CoRR Yoshua Bengio, Nicholas Léonard, Aaron C. Courville
2013	—	`ch.`	Evaluating and Extending Trajectory Features for Activity Recognition. Advanced Topics in Computer Vision Ross Messing, Atousa Torabi, Aaron C. Courville
2013	—	`conf`	Joint Training Deep Boltzmann Machines for Classification ICLR (Workshop) Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	Maxout Networks CoRR Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Maxout Networks. ICML (3) Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	A*	`conf`	Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines ICLR (Poster) Guillaume Desjardins, Razvan Pascanu, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Multi-Prediction Deep Boltzmann Machines. NIPS Ian J. Goodfellow, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	On the Challenges of Physical Implementations of RBMs. CoRR Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	Representation Learning: A Review and New Perspectives. IEEE Trans. Pattern Anal. Mach. Intell. Yoshua Bengio, Aaron C. Courville, Pascal Vincent
2013	J	`jnl`	Scaling Up Spike-and-Slab Models for Unsupervised Feature Learning. IEEE Trans. Pattern Anal. Mach. Intell. Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	A	`conf`	Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions. AISTATS Heng Luo, Pierre Luc Carrier, Aaron C. Courville, Yoshua Bengio
2012	—	`conf`	Disentangling Factors of Variation for Facial Expression Recognition. ECCV (6) Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza
2012	J	`jnl`	Disentangling Factors of Variation via Generative Entangling CoRR Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Efficient EM Training of Gaussian Mixtures with Missing Data CoRR Olivier Delalleau, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Joint Training of Deep Boltzmann Machines CoRR Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	A*	`conf`	Large-Scale Feature Learning With Spike-and-Slab Sparse Coding. ICML Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	On Training Deep Boltzmann Machines CoRR Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery CoRR Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions CoRR Heng Luo, Pierre Luc Carrier, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives CoRR Yoshua Bengio, Aaron C. Courville, Pascal Vincent
2012	—	`conf`	Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning 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, James Bergstra
2011	A	`conf`	A Spike and Slab Restricted Boltzmann Machine. AISTATS Aaron C. Courville, James Bergstra, Yoshua Bengio
2011	J	`jnl`	A bistable computational model of recurring epileptiform activity as observed in rodent slice preparations. Neural Networks Robert D. Vincent, Aaron C. Courville, Joelle Pineau
2011	—	`conf`	On Tracking The Partition Function. NIPS Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio
2011	J	`jnl`	The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All) CoRR James Bergstra, Aaron C. Courville, Yoshua Bengio
2011	A*	`conf`	Unsupervised Models of Images by Spikeand-Slab RBMs. ICML Aaron C. Courville, James Bergstra, Yoshua Bengio
2010	J	`jnl`	Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs CoRR Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio
2010	A	`conf`	Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines. AISTATS Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau
2010	J	`jnl`	Why Does Unsupervised Pre-training Help Deep Learning? J. Mach. Learn. Res. Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio
2010	A	`conf`	Why Does Unsupervised Pre-training Help Deep Learning? AISTATS Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent
2009	—	`conf`	An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism. NIPS Aaron C. Courville, Douglas Eck, Yoshua Bengio
2007	A*	`conf`	An empirical evaluation of deep architectures on problems with many factors of variation. ICML Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
2007	—	`conf`	The rat as particle filter. NIPS Nathaniel D. Daw, Aaron C. Courville
2006	J	`jnl`	A Generative Model of Terrain for Autonomous Navigation in Vegetation. Int. J. Robotics Res. Carl Wellington, Aaron C. Courville, Anthony Stentz
2006	J	`jnl`	Representation and Timing in Theories of the Dopamine System. Neural Comput. Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
2005	—	`conf`	Interacting Markov Random Fields for Simultaneous Terrain Modeling and Obstacle Detection. Robotics: Science and Systems Carl Wellington, Aaron C. Courville, Anthony Stentz
2004	—	`conf`	Similarity and Discrimination in Classical Conditioning: A Latent Variable Account. NIPS Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
2003	—	`conf`	Model Uncertainty in Classical Conditioning. NIPS Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. Gordon, David S. Touretzky
2002	—	`conf`	Timing and Partial Observability in the Dopamine System. NIPS Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
2001	—	`conf`	Modeling Temporal Structure in Classical Conditioning. NIPS Aaron C. Courville, David S. Touretzky