Marc G. Bellemare

126 papers A* 43A 5B 1C 1Journal 68Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Compositional Planning with Jumpy World Models. CoRR Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Marc G. Bellemare, Alessandro Lazaric, Ahmed Touati
2025	J	`jnl`	Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning. CoRR Yash Jhaveri, Harley Wiltzer, Patrick Shafto, Marc G. Bellemare, David Meger
2025	J	`jnl`	Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs. CoRR Nicolas Le Roux, Marc G. Bellemare, Jonathan Lebensold, Arnaud Bergeron, Joshua Greaves, Alexandre Fréchette, Carolyne Pelletier, Eric Thibodeau-Laufer, Sándor Tóth, Sam Work
2024	A*	`conf`	A Distributional Analogue to the Successor Representation. ICML Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
2024	J	`jnl`	A Distributional Analogue to the Successor Representation. CoRR Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
2024	A*	`conf`	Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning. NeurIPS Harley Wiltzer, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri
2024	J	`jnl`	Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning. CoRR Harley Wiltzer, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri
2024	J	`jnl`	An Analysis of Quantile Temporal-Difference Learning. J. Mach. Learn. Res. Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney
2024	J	`jnl`	Controlling Large Language Model Agents with Entropic Activation Steering. CoRR Nate Rahn, Pierluca D'Oro, Marc G. Bellemare
2023	A	`conf`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2023	J	`jnl`	An Analysis of Quantile Temporal-Difference Learning. CoRR Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney
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	A*	`conf`	Bootstrapped Representations in Reinforcement Learning. ICML Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney
2023	J	`jnl`	Bootstrapped Representations in Reinforcement Learning. CoRR Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney
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	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	A*	`conf`	Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control. NeurIPS Nate Rahn, Pierluca D'Oro, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare
2023	J	`jnl`	Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control. CoRR Nate Rahn, Pierluca D'Oro, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare
2023	A*	`conf`	Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. ICLR Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2023	J	`jnl`	Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. CoRR Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
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`	Small batch deep reinforcement learning. NeurIPS Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	J	`jnl`	Small batch deep reinforcement learning. CoRR Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	—	`conf`	The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning. Tiny Papers @ ICLR Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	A*	`conf`	The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation. ICML Mark Rowland, Yunhao Tang, Clare Lyle, Rémi Munos, Marc G. Bellemare, Will Dabney
2023	J	`jnl`	The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation. CoRR Mark Rowland, Yunhao Tang, Clare Lyle, Rémi Munos, Marc G. Bellemare, Will Dabney
2022	J	`jnl`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
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`	Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning. ICML Harley E. Wiltzer, David Meger, Marc G. Bellemare
2022	J	`jnl`	Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning. CoRR Harley Wiltzer, David Meger, Marc G. Bellemare
2022	A	`conf`	On the Generalization of Representations in Reinforcement Learning. AISTATS Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare
2022	J	`jnl`	On the Generalization of Representations in Reinforcement Learning. CoRR Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare
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`	The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning. NeurIPS Yunhao Tang, Rémi Munos, Mark Rowland, Bernardo Ávila Pires, Will Dabney, Marc G. Bellemare
2022	J	`jnl`	The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning. CoRR Yunhao Tang, Mark Rowland, Rémi Munos, Bernardo Ávila Pires, Will Dabney, Marc G. Bellemare
2021	A*	`conf`	Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning. ICLR Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare
2021	J	`jnl`	Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning. CoRR Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare
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`	Metrics and Continuity in Reinforcement Learning. AAAI Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
2021	J	`jnl`	Metrics and continuity in reinforcement learning. CoRR Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
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`	The Importance of Pessimism in Fixed-Dataset Policy Optimization. ICLR Jacob Buckman, Carles Gelada, Marc G. Bellemare
2021	A*	`conf`	The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. AAAI Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
2020	A	`conf`	A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms. AISTATS Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare
2020	J	`jnl`	A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms. CoRR Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare
2020	A*	`conf`	Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction. AAAI Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
2020	J	`jnl`	Autonomous navigation of stratospheric balloons using reinforcement learning. Nat. Marc G. Bellemare, Salvatore Candido, Pablo Samuel Castro, Jun Gong, Marlos C. Machado, Subhodeep Moitra, Sameera S. Ponda, Ziyu Wang
2020	A*	`conf`	Count-Based Exploration with the Successor Representation. AAAI Marlos C. Machado, Marc G. Bellemare, Michael Bowling
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`	On Catastrophic Interference in Atari 2600 Games. CoRR William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
2020	A*	`conf`	Representations for Stable Off-Policy Reinforcement Learning. ICML Dibya Ghosh, Marc G. Bellemare
2020	J	`jnl`	Representations for Stable Off-Policy Reinforcement Learning. CoRR Dibya Ghosh, Marc G. Bellemare
2020	C	`conf`	Shaping the Narrative Arc: Information-Theoretic Collaborative DialoguePaper type: Technical Paper. ICCC Kory Wallace Mathewson, Pablo Samuel Castro, Colin Cherry, George F. Foster, Marc G. Bellemare
2020	J	`jnl`	The Hanabi challenge: A new frontier for AI research. Artif. Intell. Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
2020	J	`jnl`	The Importance of Pessimism in Fixed-Dataset Policy Optimization. CoRR Jacob Buckman, Carles Gelada, Marc G. Bellemare
2020	J	`jnl`	The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. CoRR Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
2020	J	`jnl`	Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces. CoRR Ahmed Touati, Adrien Ali Taïga, Marc G. Bellemare
2019	A*	`conf`	A Comparative Analysis of Expected and Distributional Reinforcement Learning. AAAI Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro
2019	J	`jnl`	A Comparative Analysis of Expected and Distributional Reinforcement Learning. CoRR Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare
2019	A*	`conf`	A Geometric Perspective on Optimal Representations for Reinforcement Learning. NeurIPS Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle
2019	J	`jnl`	A Geometric Perspective on Optimal Representations for Reinforcement Learning. CoRR Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle
2019	J	`jnl`	Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction. CoRR Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
2019	A*	`conf`	An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. IJCAI Felipe Petroski Such, Vashisht Madhavan, Rosanne Liu, Rui Wang, Pablo Samuel Castro, Yulun Li, Jiale Zhi, Ludwig Schubert, Marc G. Bellemare, Jeff Clune, Joel Lehman
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	A*	`conf`	DeepMDP: Learning Continuous Latent Space Models for Representation Learning. ICML Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare
2019	J	`jnl`	DeepMDP: Learning Continuous Latent Space Models for Representation Learning. CoRR Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare
2019	A	`conf`	Distributional reinforcement learning with linear function approximation. AISTATS Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra
2019	J	`jnl`	Distributional reinforcement learning with linear function approximation. CoRR Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra
2019	J	`jnl`	Hyperbolic Discounting and Learning over Multiple Horizons. CoRR William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle
2019	A*	`conf`	Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift. AAAI Carles Gelada, Marc G. Bellemare
2019	J	`jnl`	Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift. CoRR Carles Gelada, Marc G. Bellemare
2019	J	`jnl`	Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue. CoRR Kory W. Mathewson, Pablo Samuel Castro, Colin Cherry, George F. Foster, Marc G. Bellemare
2019	A*	`conf`	Statistics and Samples in Distributional Reinforcement Learning. ICML Mark Rowland, Robert Dadashi, Saurabh Kumar, Rémi Munos, Marc G. Bellemare, Will Dabney
2019	J	`jnl`	Statistics and Samples in Distributional Reinforcement Learning. CoRR Mark Rowland, Robert Dadashi, Saurabh Kumar, Rémi Munos, Marc G. Bellemare, Will Dabney
2019	—	`conf`	Temporally Extended Metrics for Markov Decision Processes. SafeAI@AAAI Philip Amortila, Marc G. Bellemare, Prakash Panangaden, Doina Precup
2019	J	`jnl`	The Hanabi Challenge: A New Frontier for AI Research. CoRR Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
2019	A*	`conf`	The Value Function Polytope in Reinforcement Learning. ICML Robert Dadashi, Marc G. Bellemare, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans
2019	J	`jnl`	The Value Function Polytope in Reinforcement Learning. CoRR Robert Dadashi, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare
2018	A	`conf`	An Analysis of Categorical Distributional Reinforcement Learning. AISTATS Mark Rowland, Marc G. Bellemare, Will Dabney, Rémi Munos, Yee Whye Teh
2018	J	`jnl`	An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. CoRR Felipe Petroski Such, Vashisht Madhavan, Rosanne Liu, Rui Wang, Pablo Samuel Castro, Yulun Li, Ludwig Schubert, Marc G. Bellemare, Jeff Clune, Joel Lehman
2018	J	`jnl`	An Introduction to Deep Reinforcement Learning. CoRR Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
2018	J	`jnl`	An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
2018	J	`jnl`	Approximate Exploration through State Abstraction. CoRR Adrien Ali Taïga, Aaron C. Courville, Marc G. Bellemare
2018	J	`jnl`	Count-Based Exploration with the Successor Representation. CoRR Marlos C. Machado, Marc G. Bellemare, Michael Bowling
2018	A*	`conf`	Distributional Reinforcement Learning With Quantile Regression. AAAI Will Dabney, Mark Rowland, Marc G. Bellemare, Rémi Munos
2018	J	`jnl`	Dopamine: A Research Framework for Deep Reinforcement Learning. CoRR Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare
2018	A*	`conf`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2018	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2018	J	`jnl`	The Barbados 2018 List of Open Issues in Continual Learning. CoRR Tom Schaul, Hado van Hasselt, Joseph Modayil, Martha White, Adam White, Pierre-Luc Bacon, Jean Harb, Shibl Mourad, Marc G. Bellemare, Doina Precup
2018	—	`conf`	The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning. ICLR (Poster) Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar, Bilal Piot, Marc G. Bellemare, Rémi Munos
2017	A*	`conf`	A Distributional Perspective on Reinforcement Learning. ICML Marc G. Bellemare, Will Dabney, Rémi Munos
2017	J	`jnl`	A Distributional Perspective on Reinforcement Learning. CoRR Marc G. Bellemare, Will Dabney, Rémi Munos
2017	A*	`conf`	A Laplacian Framework for Option Discovery in Reinforcement Learning. ICML Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling
2017	J	`jnl`	A Laplacian Framework for Option Discovery in Reinforcement Learning. CoRR Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling
2017	A*	`conf`	Automated Curriculum Learning for Neural Networks. ICML Alex Graves, Marc G. Bellemare, Jacob Menick, Rémi Munos, Koray Kavukcuoglu
2017	J	`jnl`	Automated Curriculum Learning for Neural Networks. CoRR Alex Graves, Marc G. Bellemare, Jacob Menick, Rémi Munos, Koray Kavukcuoglu
2017	A*	`conf`	Count-Based Exploration with Neural Density Models. ICML Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
2017	J	`jnl`	Count-Based Exploration with Neural Density Models. CoRR Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
2017	J	`jnl`	Distributional Reinforcement Learning with Quantile Regression. CoRR Will Dabney, Mark Rowland, Marc G. Bellemare, Rémi Munos
2017	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2017	J	`jnl`	The Cramer Distance as a Solution to Biased Wasserstein Gradients. CoRR Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos
2017	J	`jnl`	The Reactor: A Sample-Efficient Actor-Critic Architecture. CoRR Audrunas Gruslys, Mohammad Gheshlaghi Azar, Marc G. Bellemare, Rémi Munos
2016	A*	`conf`	Increasing the Action Gap: New Operators for Reinforcement Learning. AAAI Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
2016	J	`jnl`	Q($λ$) with Off-Policy Corrections. CoRR Anna Harutyunyan, Marc G. Bellemare, Tom Stepleton, Rémi Munos
2016	B	`conf`	Q(λ) with Off-Policy Corrections. ALT Anna Harutyunyan, Marc G. Bellemare, Tom Stepleton, Rémi Munos
2016	—	`conf`	Safe and Efficient Off-Policy Reinforcement Learning. NIPS Rémi Munos, Tom Stepleton, Anna Harutyunyan, Marc G. Bellemare
2016	J	`jnl`	Safe and Efficient Off-Policy Reinforcement Learning. CoRR Rémi Munos, Tom Stepleton, Anna Harutyunyan, Marc G. Bellemare
2016	—	`conf`	Unifying Count-Based Exploration and Intrinsic Motivation. NIPS Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
2016	J	`jnl`	Unifying Count-Based Exploration and Intrinsic Motivation. CoRR Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
2015	A*	`conf`	Compress and Control. AAAI Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2015	A*	`conf`	Count-Based Frequency Estimation with Bounded Memory. IJCAI Marc G. Bellemare
2015	J	`jnl`	Human-level control through deep reinforcement learning. Nat. Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
2015	J	`jnl`	Increasing the Action Gap: New Operators for Reinforcement Learning. CoRR Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
2015	—	`ed.`	Learning for General Competency in Video Games, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 26, 2015. AAAI Workshop: Learning for General Competency in Video Games Michael Bowling, Marc G. Bellemare, Erik Talvitie, Joel Veness, Marlos C. Machado
2015	A*	`conf`	Online Learning of k-CNF Boolean Functions. IJCAI Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
2015	A*	`conf`	The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract). IJCAI Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2014	J	`jnl`	Compress and Control. CoRR Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2014	A*	`conf`	Skip Context Tree Switching. ICML Marc G. Bellemare, Joel Veness, Erik Talvitie
2013	—	`conf`	Bayesian Learning of Recursively Factored Environments. ICML (3) Marc G. Bellemare, Joel Veness, Michael Bowling
2013	J	`jnl`	The Arcade Learning Environment: An Evaluation Platform for General Agents. J. Artif. Intell. Res. Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2012	A*	`conf`	Investigating Contingency Awareness Using Atari 2600 Games. AAAI Marc G. Bellemare, Joel Veness, Michael Bowling
2012	—	`conf`	Sketch-Based Linear Value Function Approximation. NIPS Marc G. Bellemare, Joel Veness, Michael Bowling
2012	J	`jnl`	The Arcade Learning Environment: An Evaluation Platform for General Agents CoRR Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2007	A*	`conf`	Context-Driven Predictions. IJCAI Marc G. Bellemare, Doina Precup