| Dueling Network Architectures for Deep Reinforcement Learning Z Wang, T Schaul, M Hessel, H Van Hasselt, M Lanctot, N De Freitas International Conference on Machine Learning (ICML 2016), 1995–2003, 2016 | 5158 | 2016 |
| Rainbow: Combining Improvements in Deep Reinforcement Learning M Hessel, J Modayil, H van Hasselt, T Schaul, G Ostrovski, W Dabney, ... Association for the Advancement of Artificial Intelligence (AAAI 2018), 2017 | 2738 | 2017 |
| Distributed Prioritized Experience Replay D Horgan, J Quan, D Budden, G Barth-Maron, M Hessel, H van Hasselt, ... International Conference on Learning Representations (ICLR 2018), 2018 | 901 | 2018 |
| Multi-task Deep Reinforcement Learning with PopArt M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt Association for the Advancement of Artificial Intelligence (AAAI 2019), 2018 | 315 | 2018 |
| The predictron: End-to-end learning and planning D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ... International Conference on Machine Learning (ICML 2017), 3191--3199, 2016 | 308 | 2016 |
| Deep Reinforcement Learning and the Deadly Triad H van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil Deep Reinforcement Learning Workshop (NeurIPS 2018), 2018 | 263 | 2018 |
| When to use parametric models in reinforcement learning? HP van Hasselt, M Hessel, J Aslanides Advances in Neural Information Processing Systems (NeurIPS 2019), 2019 | 223 | 2019 |
| Learning values across many orders of magnitude HP van Hasselt, A Guez, M Hessel, V Mnih, D Silver Advances In Neural Information Processing Systems (NIPS 2016), 4287-4295, 2016 | 199 | 2016 |
| Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement A Barreto, D Borsa, J Quan, T Schaul, D Silver, M Hessel, D Mankowitz, ... International Conference on Machine Learning (ICML 2018), 510-519, 2018 | 197 | 2018 |
| Behaviour Suite for Reinforcement Learning I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ... International Conference on Learning Representations (ICLR 2020), 2019 | 184 | 2019 |
| Discovering reinforcement learning algorithms J Oh, M Hessel, WM Czarnecki, Z Xu, HP van Hasselt, S Singh, D Silver Advances in Neural Information Processing Systems 33, 1060-1070, 2020 | 153 | 2020 |
| Observe and Look Further: Achieving Consistent Performance on Atari T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ... arXiv preprint arXiv:1805.11593, 2018 | 140 | 2018 |
| The DeepMind JAX Ecosystem, 2020 I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ... URL http://github. com/deepmind 18, 2010 | 99 | 2010 |
| Discovery of useful questions as auxiliary tasks V Veeriah, M Hessel, Z Xu, J Rajendran, RL Lewis, J Oh, HP van Hasselt, ... Advances in Neural Information Processing Systems (NeurIPS 2019), 9310-9321, 2019 | 95 | 2019 |
| What Can Learned Intrinsic Rewards Capture? Z Zheng, J Oh, M Hessel, Z Xu, M Kroiss, H van Hasselt, D Silver, S Singh International Conference on Machine Learning (ICML 2020), 0 | 92* | |
| A self-tuning actor-critic algorithm T Zahavy, Z Xu, V Veeriah, M Hessel, J Oh, HP van Hasselt, D Silver, ... Advances in neural information processing systems 33, 20913-20924, 2020 | 86 | 2020 |
| Muesli: Combining improvements in policy optimization M Hessel, I Danihelka, F Viola, A Guez, S Schmitt, L Sifre, T Weber, ... International Conference on Machine Learning, 4214-4226, 2021 | 80 | 2021 |
| Meta-gradient reinforcement learning with an objective discovered online Z Xu, HP van Hasselt, M Hessel, J Oh, S Singh, D Silver Advances in Neural Information Processing Systems 33, 15254-15264, 2020 | 78 | 2020 |
| Off-Policy Actor-Critic with Shared Experience Replay S Schmitt, M Hessel, K Simonyan International Conference on Machine Learning (ICML 2020), 2019 | 52 | 2019 |
| Optax: composable gradient transformation and optimisation M Hessel, D Budden, F Viola, M Rosca, E Sezener, T Hennigan JAX, http://github. com/deepmind/optax (last access: 4 July 2023), version 0.0 1, 2020 | 49 | 2020 |
Hado van HasseltResearch Scientist, DeepMind; Honorary Professor, UCLDirección de correo verificada de google.com
