Bernardo Avila Pires

13 papers · 2013–2025 · 5 venues · across top CS/AI venues

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Achievements

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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (23)

💎 Century Club · Bronze 🚀 Conference Pioneer 🗃️ Keyword Collector (64)

Venues

ICML (7) NeurIPS (3) AISTATS (1) COLT (1) JMLR (1)

Top co-authors

Rémi Munos (9) Yunhao Tang (7) Mark Rowland (7) Zhaohan Daniel Guo (6) Michal Valko (6) Bilal Piot (6) Will Dabney (5) Mohammad Gheshlaghi azar (4) Daniele Calandriello (4) Pierre Harvey Richemond (3)

Research topics

Machine Learning (12) Reinforcement Learning (10) Methods (10) Learning Types · Machine Learning (7) Optimization & Theory (6) Artificial Intelligence (5) Deep Learning (5) Learning Types · Deep Learning (5) Core AI (4) Core Methods (3) Applications (1) Learning Paradigms (1)

Keywords

reinforcement learning (4) representation learning (3) self-supervised learning (3) deep reinforcement learning (3) policy optimization (2) off-policy learning (2) multi-step learning (2) latent representation (2) ipo (2) low-rank approximation (1) distributional reinforcement learning (1) loss landscape (1) preference optimization (1) markov decision process (1) model-based reinforcement learning (1) contrastive learning (1) quantile regression (1) value iteration (1) policy gradient (1) value function (1)

Papers

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning AISTATS 2025 Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025 Generalized Preference Optimization: A Unified Approach to Offline Alignment ICML 2024 Human Alignment of Large Language Models through Online Preference Optimisation ICML 2024 DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm ICML 2023 Understanding Plasticity in Neural Networks ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023 BYOL-Explore: Exploration by Bootstrapped Prediction NeurIPS 2022 The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning NeurIPS 2022 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning ICML 2020 Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning NeurIPS 2020 Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models COLT 2016 Cost-sensitive Multiclass Classification Risk Bounds ICML 2013