van Hasselt, Hado

31 publications

NeurIPS 2025 DataRater: Meta-Learned Dataset Curation Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeff Dean, Hado van Hasselt, David Silver

AAAI 2025 General Uncertainty Estimation with Delta Variances Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

ICML 2025 Scalable Meta-Learning via Mixed-Mode Differentiation Iurii Kemaev, Dan A. Calian, Luisa M Zintgraf, Gregory Farquhar, Hado Van Hasselt

ICML 2025 Wasserstein Policy Optimization David Pfau, Ian Davies, Diana L Borsa, João Guilherme Madeira Araújo, Brendan Daniel Tracey, Hado Van Hasselt

TMLR 2024 A Survey of Temporal Credit Assignment in Deep Reinforcement Learning Eduardo Pignatelli, Johan Ferret, Matthieu Geist, Thomas Mesnard, Hado van Hasselt, Laura Toni

CoLLAs 2024 Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle, Zeyu Zheng, Khimya Khetarpal, Hado van Hasselt, Razvan Pascanu, James Martens, Will Dabney

NeurIPS 2024 Normalization and Effective Learning Rates in Reinforcement Learning Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney

AAAI 2023 Exploration via Epistemic Value Estimation Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

ICLR 2023 Human-Level Atari 200x Faster Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt, Charles Blundell, Adria Puigdomenech Badia

ICLRW 2023 Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt

ICLR 2022 Bootstrapped Meta-Learning Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh

AAAI 2022 Chaining Value Functions for Off-Policy Learning Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

AAAI 2022 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

AAAI 2022 Learning Expected Emphatic Traces for Deep RL Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt

ICLR 2022 Learning by Directional Gradient Descent David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt

NeurIPSW 2022 Optimistic Meta-Gradients Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado van Hasselt, András György, Satinder Singh

NeurIPSW 2021 Bootstrapped Meta-Learning Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh

ICML 2021 Emphatic Algorithms for Deep Reinforcement Learning Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado Van Hasselt

AAAI 2021 Expected Eligibility Traces Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa

NeurIPSW 2021 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

NeurIPSW 2021 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

ICML 2021 Muesli: Combining Improvements in Policy Optimization Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado Van Hasselt

ICLR 2020 Behaviour Suite for Reinforcement Learning Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt

ICML 2020 What Can Learned Intrinsic Rewards Capture? Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado Van Hasselt, David Silver, Satinder Singh

AAAI 2019 Multi-Task Deep Reinforcement Learning with PopArt Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt, Hado van Hasselt

ICLR 2019 Universal Successor Features Approximators Diana Borsa, Andre Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Remi Munos, David Silver, Tom Schaul

ICLR 2018 Distributed Prioritized Experience Replay Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver

AAAI 2018 Rainbow: Combining Improvements in Deep Reinforcement Learning Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver

AAAI 2016 Deep Reinforcement Learning with Double Q-Learning Hado van Hasselt, Arthur Guez, David Silver

UAI 2014 Off-Policy TD( L) with a True Online Equivalence Hado van Hasselt, Ashique Rupam Mahmood, Richard S. Sutton

JMLR 2011 Exploiting Best-Match Equations for Efficient Reinforcement Learning Harm van Seijen, Shimon Whiteson, Hado van Hasselt, Marco Wiering