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Andre Barreto

31 papers · 2011–2025 · 6 venues · across top CS/AI venues

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Achievements

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+13 more ↓ πŸ—ΊοΈ Taxonomy Completionist (44) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Half πŸŒ‰ Interdisciplinary Bridge Β· Gold 🐣 Hot Topic Early Bird
πŸ”¬ Deep Specialist (20) πŸ† Grand Slam 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion (5) 🧭 Keyword Pioneer πŸ“ˆ Trend Setter ⚑ Prolific Year Β· Productive πŸ—ƒοΈ Keyword Collector (127) πŸ’Ž Century Club Β· Bronze πŸ”₯ Unstoppable Β· Bronze 🌈 Renaissance Researcher (5)

Venues

NeurIPS (15) ICML (7) ICLR (4) AAAI (2) JMLR (2) AISTATS (1)

Top co-authors

David Silver (10) Will Dabney (8) Tom Schaul (7) Diana Borsa (7) Doina Precup (6) RΓ©mi Munos (5) Satinder P. Singh (5) Mark Rowland (4) John Quan (4) Georg Ostrovski (3)

Research topics

Reinforcement Learning (28) Methods (26) Machine Learning (20) Learning Types Β· Machine Learning (15) Artificial Intelligence (14) Core AI (11) Applications (9) Optimization & Theory (9) Core Methods (8) Learning Paradigms (6) Deep Learning (5) Learning Types Β· Deep Learning (4) Healthcare & Medicine (1) Mathematics & Optimization (1) Robotics (1)

Keywords

reinforcement learning (12) value function (8) deep reinforcement learning (7) successor feature (7) transfer learning (6) model-based reinforcement learning (6) policy improvement (5) value function approximation (4) value iteration (3) generalized policy improvement (3) value equivalence (3) temporal difference learning (2) generative model (2) function approximation (2) bellman operator (2) successor representation (2) policy learning (2) representation learning (2) policy iteration (2) hierarchical reinforcement learning (2)

Papers

Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025 A Distributional Analogue to the Successor Representation ICML 2024 Position: Video as the New Language for Real-World Decision Making ICML 2024 A Definition of Continual Reinforcement Learning NeurIPS 2023 Deep Reinforcement Learning with Plasticity Injection NeurIPS 2023 Temporal Abstraction in Reinforcement Learning with the Successor Representation JMLR 2023 Approximate Value Equivalence NeurIPS 2022 Generalised Policy Improvement with Geometric Policy Composition ICML 2022 Model-Value Inconsistency as a Signal for Epistemic Uncertainty ICML 2022 The Phenomenon of Policy Churn NeurIPS 2022 Discovering a set of policies for the worst case reward ICLR 2021 Expected Eligibility Traces AAAI 2021 Proper Value Equivalence NeurIPS 2021 Risk-Aware Transfer in Reinforcement Learning using Successor Features NeurIPS 2021 Temporally-Extended Ξ΅-Greedy Exploration ICLR 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021 Fast Task Inference with Variational Intrinsic Successor Features ICLR 2020 On Efficiency in Hierarchical Reinforcement Learning NeurIPS 2020 The Value Equivalence Principle for Model-Based Reinforcement Learning NeurIPS 2020 Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates NeurIPS 2019 Composing Entropic Policies using Divergence Correction ICML 2019 The Option Keyboard: Combining Skills in Reinforcement Learning NeurIPS 2019 Universal Successor Features Approximators ICLR 2019 Fast deep reinforcement learning using online adjustments from the past NeurIPS 2018 Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement ICML 2018 Natural Value Approximators: Learning when to Trust Past Estimates NeurIPS 2017 Successor Features for Transfer in Reinforcement Learning NeurIPS 2017 The Predictron: End-To-End Learning and Planning ICML 2017 Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017 On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NeurIPS 2012 Reinforcement Learning using Kernel-Based Stochastic Factorization NeurIPS 2011