Pablo Samuel Castro

117 papers A* 32A 4C 3Journal 72Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Align and Filter: Improving Performance in Asynchronous On-Policy RL. CoRR Homayoun Honari, Roger Creus Castanyer, Michael Przystupa, Michael Noukhovitch, Pablo Samuel Castro, Glen Berseth
2026	J	`jnl`	Discovering Differences in Strategic Behavior Between Humans and LLMs. CoRR Caroline Wang, Daniel Kasenberg, Kim Stachenfeld, Pablo Samuel Castro
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
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`	A Survey of State Representation Learning for Deep Reinforcement Learning. CoRR Ayoub Echchahed, Pablo Samuel Castro
2025	J	`jnl`	A Survey of State Representation Learning for Deep Reinforcement Learning. Trans. Mach. Learn. Res. Ayoub Echchahed, Pablo Samuel Castro
2025	J	`jnl`	ARM-FM: Automated Reward Machines via Foundation Models for Compositional Reinforcement Learning. CoRR Roger Creus Castanyer, Faisal Mohamed, Pablo Samuel Castro, Cyrus Neary, Glen Berseth
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`	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	J	`jnl`	Continual Learning in Vision-Language Models via Aligned Model Merging. CoRR Ghada Sokar, Gintare Karolina Dziugaite, Anurag Arnab, Ahmet Iscen, Pablo Samuel Castro, Cordelia Schmid
2025	A*	`conf`	Discovering Symbolic Cognitive Models from Human and Animal Behavior. ICML Pablo Samuel Castro, Nenad Tomasev, Ankit Anand, Navodita Sharma, Rishika Mohanta, Aparna Dev, Kuba Perlin, Siddhant Jain, Kyle Levin, Noémi Élteto, Will Dabney, Alexander Novikov, Glenn C. Turner, Maria K. Eckstein, Nathaniel D. Daw, Kevin J. Miller, Kim Stachenfeld
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`	Estimating Policy Functions in Payment Systems Using Reinforcement Learning. ACM Trans. Economics and Comput. Pablo Samuel Castro, Ajit Desai, Han Du, Rodney Garratt, Francisco Rivadeneyra
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	J	`jnl`	Meta-World+: An Improved, Standardized, RL Benchmark. CoRR Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Tianhe Yu, Zhanpeng He, K. R. Zentner, Ryan Julian, Jordan K. Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro
2025	J	`jnl`	Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning. CoRR Ghada Sokar, Pablo Samuel Castro
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`	Multi-Task Reinforcement Learning Enables Parameter Scaling. CoRR Reginald McLean, Evangelos Chatzaroulas, J. K. Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro
2025	J	`jnl`	Optimistic critics can empower small actors. CoRR Olya Mastikhina, Dhruv Sreenivas, Pablo Samuel Castro
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	A*	`conf`	Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning. ICLR Samuel Garcin, Trevor McInroe, Pablo Samuel Castro, Christopher G. Lucas, David Abel, Prakash Panangaden, Stefano V. Albrecht
2025	J	`jnl`	Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning. CoRR Samuel Garcin, Trevor McInroe, Pablo Samuel Castro, Prakash Panangaden, Christopher G. Lucas, David Abel, Stefano V. Albrecht
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	J	`jnl`	The Formalism-Implementation Gap in Reinforcement Learning Research. CoRR Pablo Samuel Castro
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
2024	J	`jnl`	A density estimation perspective on learning from pairwise human preferences. Trans. Mach. Learn. Res. Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
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	A*	`conf`	CALE: Continuous Arcade Learning Environment. NeurIPS Jesse Farebrother, Pablo Samuel Castro
2024	J	`jnl`	CALE: Continuous Arcade Learning Environment. CoRR Jesse Farebrother, Pablo Samuel Castro
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	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	—	`conf`	Jaxpruner: A Concise Library for Sparsity Research. CPAL Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
2024	J	`jnl`	Mixture of Experts in a Mixture of RL settings. RLJ Timon Willi, Johan S. Obando-Ceron, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Pablo Samuel Castro
2024	J	`jnl`	Mixture of Experts in a Mixture of RL settings. CoRR Timon Willi, Johan S. Obando-Ceron, Jakob N. Foerster, Karolina Dziugaite, Pablo Samuel Castro
2024	A*	`conf`	Mixtures of Experts Unlock Parameter Scaling for Deep RL. ICML Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024	J	`jnl`	Mixtures of Experts Unlock Parameter Scaling for Deep RL. CoRR Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024	J	`jnl`	NAVIX: Scaling MiniGrid Environments with JAX. CoRR Eduardo Pignatelli, Jarek Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, Laura Toni
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	A*	`conf`	Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. ICML Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal
2024	J	`jnl`	Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. CoRR Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal
2023	J	`jnl`	A Kernel Perspective on Behavioural Metrics for Markov Decision Processes. CoRR Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland
2023	J	`jnl`	A Kernel Perspective on Behavioural Metrics for Markov Decision Processes. Trans. Mach. Learn. Res. Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland
2023	J	`jnl`	A density estimation perspective on learning from pairwise human preferences. CoRR Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
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`	JaxPruner: A concise library for sparsity research. CoRR Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
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`	Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. NeurIPS Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo Perez-Vicente, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan K. Terry
2023	J	`jnl`	Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. CoRR Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo de Lazcano, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan K. Terry
2023	—	`conf`	Offline Reinforcement Learning with On-Policy Q-Function Regularization. ECML/PKDD (4) Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist
2023	J	`jnl`	Offline Reinforcement Learning with On-Policy Q-Function Regularization. CoRR Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist
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`	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	A*	`conf`	The Dormant Neuron Phenomenon in Deep Reinforcement Learning. ICML Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci
2023	J	`jnl`	The Dormant Neuron Phenomenon in Deep Reinforcement Learning. CoRR Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci
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
2022	A	`conf`	A general class of surrogate functions for stable and efficient reinforcement learning. AISTATS Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
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`	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 State of Sparse Training in Deep Reinforcement Learning. ICML Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro
2022	J	`jnl`	The State of Sparse Training in Deep Reinforcement Learning. CoRR Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro
2021	J	`jnl`	A functional mirror ascent view of policy gradient methods with function approximation. CoRR Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
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	J	`jnl`	Losses, Dissonances, and Distortions. CoRR Pablo Samuel Castro
2021	A*	`conf`	MICo: Improved representations via sampling-based state similarity for Markov decision processes. NeurIPS Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland
2021	J	`jnl`	MICo: Learning improved representations via sampling-based state similarity for Markov decision processes. CoRR Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland
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	A*	`conf`	Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. ICML Johan S. Obando-Ceron, Pablo Samuel Castro
2021	A*	`conf`	The Difficulty of Passive Learning in Deep Reinforcement Learning. NeurIPS Georg Ostrovski, Pablo Samuel Castro, Will Dabney
2021	J	`jnl`	The Difficulty of Passive Learning in Deep Reinforcement Learning. CoRR Georg Ostrovski, Pablo Samuel Castro, Will Dabney
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	J	`jnl`	GANterpretations. CoRR Pablo Samuel Castro
2020	J	`jnl`	Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. CoRR Johan S. Obando-Ceron, Pablo Samuel Castro
2020	A*	`conf`	Rigging the Lottery: Making All Tickets Winners. ICML Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
2020	A*	`conf`	Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes. AAAI Pablo Samuel Castro
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
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	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	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`	Inverse Reinforcement Learning with Multiple Ranked Experts. CoRR Pablo Samuel Castro, Shijian Li, Daqing Zhang
2019	C	`conf`	Performing Structured Improvisations with Pre-trained Deep Learning Models. ICCC Pablo Samuel Castro
2019	J	`jnl`	Performing Structured Improvisations with pre-trained Deep Learning Models. CoRR Pablo Samuel Castro
2019	J	`jnl`	Rigging the Lottery: Making All Tickets Winners. CoRR Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
2019	J	`jnl`	Scalable methods for computing state similarity in deterministic Markov Decision Processes. CoRR Pablo Samuel Castro
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
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`	Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation. CoRR Pablo Samuel Castro, Maria Attarian
2018	J	`jnl`	Dopamine: A Research Framework for Deep Reinforcement Learning. CoRR Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare
2013	J	`jnl`	From taxi GPS traces to social and community dynamics: A survey. ACM Comput. Surv. Pablo Samuel Castro, Daqing Zhang, Chao Chen, Shijian Li, Gang Pan
2013	J	`jnl`	Real Time Anomalous Trajectory Detection and Analysis. Mob. Networks Appl. Lin Sun, Daqing Zhang, Chao Chen, Pablo Samuel Castro, Shijian Li, Zonghui Wang
2013	J	`jnl`	iBOAT: Isolation-Based Online Anomalous Trajectory Detection. IEEE Trans. Intell. Transp. Syst. Chao Chen, Daqing Zhang, Pablo Samuel Castro, Nan Li, Lin Sun, Shijian Li, Zonghui Wang
2012	J	`jnl`	Methods for computing state similarity in Markov Decision Processes. CoRR Norman Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden
2012	—	`conf`	Urban Traffic Modelling and Prediction Using Large Scale Taxi GPS Traces. Pervasive Pablo Samuel Castro, Daqing Zhang, Shijian Li
2011	—	`conf`	Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metrics. EWRL Pablo Samuel Castro, Doina Precup
2011	C	`conf`	Real-Time Detection of Anomalous Taxi Trajectories from GPS Traces. MobiQuitous Chao Chen, Daqing Zhang, Pablo Samuel Castro, Nan Li, Lin Sun, Shijian Li
2010	—	`conf`	Smarter Sampling in Model-Based Bayesian Reinforcement Learning. ECML/PKDD (1) Pablo Samuel Castro, Doina Precup
2010	A*	`conf`	Using Bisimulation for Policy Transfer in MDPs. AAAI Pablo Samuel Castro, Doina Precup
2010	A	`conf`	Using bisimulation for policy transfer in MDPs. AAMAS Pablo Samuel Castro, Doina Precup
2009	A*	`conf`	Equivalence Relations in Fully and Partially Observable Markov Decision Processes. IJCAI Pablo Samuel Castro, Prakash Panangaden, Doina Precup
2007	A*	`conf`	Using Linear Programming for Bayesian Exploration in Markov Decision Processes. IJCAI Pablo Samuel Castro, Doina Precup
2006	A	`conf`	Methods for Computing State Similarity in Markov Decision Processes. UAI Norm Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden