Will Dabney

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning AISTATS 2025 Discovering Symbolic Cognitive Models from Human and Animal Behavior ICML 2025 Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025 A Distributional Analogue to the Successor Representation ICML 2024 An Analysis of Quantile Temporal-Difference Learning JMLR 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Normalization and effective learning rates in reinforcement learning NeurIPS 2024 Bootstrapped Representations in Reinforcement Learning ICML 2023 Deep Reinforcement Learning with Plasticity Injection NeurIPS 2023 Quantile Credit Assignment ICML 2023 Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition ICML 2023 Settling the Reward Hypothesis ICML 2023 The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation ICML 2023 Understanding Plasticity in Neural Networks ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023 Generalised Policy Improvement with Geometric Policy Composition ICML 2022 Learning Dynamics and Generalization in Deep Reinforcement Learning ICML 2022 On the Expressivity of Markov Reward (Extended Abstract) IJCAI 2022 The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning NeurIPS 2022 Understanding and Preventing Capacity Loss in Reinforcement Learning ICLR 2022 Counterfactual Credit Assignment in Model-Free Reinforcement Learning ICML 2021 On the Effect of Auxiliary Tasks on Representation Dynamics AISTATS 2021 On the Expressivity of Markov Reward NeurIPS 2021 Revisiting Peng’s Q($λ$) for Modern Reinforcement Learning ICML 2021 Temporally-Extended ε-Greedy Exploration ICLR 2021 The Difficulty of Passive Learning in Deep Reinforcement Learning NeurIPS 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021 Adaptive Trade-Offs in Off-Policy Learning AISTATS 2020 Conditional Importance Sampling for Off-Policy Learning AISTATS 2020 Fast Task Inference with Variational Intrinsic Successor Features ICLR 2020 Revisiting Fundamentals of Experience Replay ICML 2020 A Geometric Perspective on Optimal Representations for Reinforcement Learning NeurIPS 2019 Hindsight Credit Assignment NeurIPS 2019 Recurrent Experience Replay in Distributed Reinforcement Learning ICLR 2019 Statistics and Samples in Distributional Reinforcement Learning ICML 2019 The Termination Critic AISTATS 2019 An Analysis of Categorical Distributional Reinforcement Learning AISTATS 2018 Autoregressive Quantile Networks for Generative Modeling ICML 2018 Distributed Distributional Deterministic Policy Gradients ICLR 2018 Implicit Quantile Networks for Distributional Reinforcement Learning ICML 2018 The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning ICLR 2018 A Distributional Perspective on Reinforcement Learning ICML 2017 Successor Features for Transfer in Reinforcement Learning NeurIPS 2017