Zhaohan Daniel Guo

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 24

Top Topics

Reinforcement Learning

Top Venues

Publications

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney
A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. CoRR (2024)
Mohammad Gheshlaghi Azar, Zhaohan Daniel Guo, Bilal Piot, Rémi Munos, Mark Rowland, Michal Valko, Daniele Calandriello
A General Theoretical Paradigm to Understand Learning from Human Preferences. AISTATS (2024)
Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Yuan Cao, Eugene Tarassov, Rémi Munos, Bernardo Ávila Pires, Michal Valko, Yong Cheng, Will Dabney
Understanding the performance gap between online and offline alignment algorithms. CoRR (2024)
Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot
Generalized Preference Optimization: A Unified Approach to Offline Alignment. CoRR (2024)
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
Nash Learning from Human Feedback. CoRR (2023)
Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition. CoRR (2023)
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
Understanding Self-Predictive Learning for Reinforcement Learning. ICML (2023)
Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition. ICML (2023)
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
BYOL-Explore: Exploration by Bootstrapped Prediction. CoRR (2022)
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
Understanding Self-Predictive Learning for Reinforcement Learning. CoRR (2022)
Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Ávila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos
Geometric Entropic Exploration. CoRR (2021)
Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell
Agent57: Outperforming the Atari Human Benchmark. ICML (2020)
Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell
Agent57: Outperforming the Atari Human Benchmark. CoRR (2020)
Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. ICML (2020)
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
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning. CoRR (2020)
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
Never Give Up: Learning Directed Exploration Strategies. CoRR (2020)
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
Never Give Up: Learning Directed Exploration Strategies. ICLR (2020)
Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. CoRR (2020)
Zhaohan Daniel Guo, Emma Brunskill
Directed Exploration for Reinforcement Learning. CoRR (2019)
Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Toby Pohlen, Rémi Munos
Neural Predictive Belief Representations. CoRR (2018)
Zhaohan Daniel Guo, Emma Brunskill
Sample Efficient Feature Selection for Factored MDPs. CoRR (2017)
Zhaohan Daniel Guo, Philip S. Thomas, Emma Brunskill
Using Options for Long-Horizon Off-Policy Evaluation. CoRR (2017)
Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
A PAC RL Algorithm for Episodic POMDPs. CoRR (2016)
Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
A PAC RL Algorithm for Episodic POMDPs. AISTATS (2016)
Zhaohan Daniel Guo, Gökhan Tür, Wen-tau Yih, Geoffrey Zweig
Joint semantic utterance classification and slot filling with recursive neural networks. SLT (2014)