Pires, Bernardo Avila

9 publications

AISTATS 2025 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney

JMLR 2025 Optimizing Return Distributions with Distributional Dynamic Programming Bernardo Ávila Pires, Mark Rowland, Diana Borsa, Zhaohan Daniel Guo, Khimya Khetarpal, André Barreto, David Abel, Rémi Munos, Will Dabney

NeurIPSW 2024 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney

NeurIPS 2022 BYOL-Explore: Exploration by Bootstrapped Prediction Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Avila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Remi Munos, Mohammad Gheshlaghi Azar, Bilal Piot

NeurIPS 2022 The Nature of Temporal Difference Errors in Multi-Step Distributional Reinforcement Learning Yunhao Tang, Remi Munos, Mark Rowland, Bernardo Avila Pires, Will Dabney, Marc Bellemare

ICML 2020 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Zhaohan Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Remi Munos, Mohammad Gheshlaghi Azar

NeurIPS 2020 Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Remi Munos, Michal Valko

COLT 2016 Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models Bernardo Ávila Pires

ICML 2012 Statistical Linear Estimation with Penalized Estimators: An Application to Reinforcement Learning Bernardo Ávila Pires, Csaba Szepesvári