Zhaohan Daniel Guo

31 papers A* 7A 3Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. AISTATS Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L. Borsa, Arthur Guez, Will Dabney
2025	J	`jnl`	Optimizing Return Distributions with Distributional Dynamic Programming. CoRR Bernardo Ávila Pires, Mark Rowland, Diana Borsa, Zhaohan Daniel Guo, Khimya Khetarpal, André Barreto, David Abel, Rémi Munos, Will Dabney
2025	J	`jnl`	Optimizing Return Distributions with Distributional Dynamic Programming. J. Mach. Learn. Res. Bernardo Ávila Pires, Mark Rowland, Diana Borsa, Zhaohan Daniel Guo, Khimya Khetarpal, André Barreto, David Abel, Rémi Munos, Will Dabney
2025	J	`jnl`	Representation Learning via Non-Contrastive Mutual Information. CoRR Zhaohan Daniel Guo, Bernardo Ávila Pires, Khimya Khetarpal, Dale Schuurmans, Bo Dai
2024	A	`conf`	A General Theoretical Paradigm to Understand Learning from Human Preferences. AISTATS Mohammad Gheshlaghi Azar, Zhaohan Daniel Guo, Bilal Piot, Rémi Munos, Mark Rowland, Michal Valko, Daniele Calandriello
2024	J	`jnl`	A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. CoRR Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney
2024	A*	`conf`	Generalized Preference Optimization: A Unified Approach to Offline Alignment. ICML Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot
2024	J	`jnl`	Generalized Preference Optimization: A Unified Approach to Offline Alignment. CoRR Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot
2024	A*	`conf`	Human Alignment of Large Language Models through Online Preference Optimisation. ICML Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot
2024	J	`jnl`	Understanding the performance gap between online and offline alignment algorithms. CoRR Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Yuan Cao, Eugene Tarassov, Rémi Munos, Bernardo Ávila Pires, Michal Valko, Yong Cheng, Will Dabney
2023	J	`jnl`	Nash Learning from Human Feedback. CoRR Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot
2023	A*	`conf`	Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition. ICML Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa
2023	J	`jnl`	Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition. CoRR Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa
2023	A*	`conf`	Understanding Self-Predictive Learning for Reinforcement Learning. ICML Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko
2022	J	`jnl`	BYOL-Explore: Exploration by Bootstrapped Prediction. CoRR Zhaohan Daniel Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Ávila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Rémi Munos, Mohammad Gheshlaghi Azar, Bilal Piot
2022	J	`jnl`	Understanding Self-Predictive Learning for Reinforcement Learning. CoRR Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko
2021	J	`jnl`	Geometric Entropic Exploration. CoRR Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Ávila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos
2020	A*	`conf`	Agent57: Outperforming the Atari Human Benchmark. ICML Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell
2020	J	`jnl`	Agent57: Outperforming the Atari Human Benchmark. CoRR Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell
2020	A*	`conf`	Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. ICML Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar
2020	J	`jnl`	Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. CoRR Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar
2020	J	`jnl`	Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning. CoRR Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko
2020	A*	`conf`	Never Give Up: Learning Directed Exploration Strategies. ICLR Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
2020	J	`jnl`	Never Give Up: Learning Directed Exploration Strategies. CoRR Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
2019	J	`jnl`	Directed Exploration for Reinforcement Learning. CoRR Zhaohan Daniel Guo, Emma Brunskill
2018	J	`jnl`	Neural Predictive Belief Representations. CoRR Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Toby Pohlen, Rémi Munos
2017	J	`jnl`	Sample Efficient Feature Selection for Factored MDPs. CoRR Zhaohan Daniel Guo, Emma Brunskill
2017	J	`jnl`	Using Options for Long-Horizon Off-Policy Evaluation. CoRR Zhaohan Daniel Guo, Philip S. Thomas, Emma Brunskill
2016	A	`conf`	A PAC RL Algorithm for Episodic POMDPs. AISTATS Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
2016	J	`jnl`	A PAC RL Algorithm for Episodic POMDPs. CoRR Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
2014	—	`conf`	Joint semantic utterance classification and slot filling with recursive neural networks. SLT Zhaohan Daniel Guo, Gökhan Tür, Wen-tau Yih, Geoffrey Zweig