Mastering atari, go, chess and shogi by planning with a learned model J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ... Nature 588 (7839), 604-609, 2020 | 2744 | 2020 |
Multi-task deep reinforcement learning with popart M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3796-3803, 2019 | 333 | 2019 |
Kickstarting deep reinforcement learning S Schmitt, JJ Hudson, A Zidek, S Osindero, C Doersch, WM Czarnecki, ... Deep Reinforcement Learning Workshop, NeurIPS, 2018 | 163 | 2018 |
Learning and Planning in Complex Action Spaces T Hubert, J Schrittwieser, I Antonoglou, M Barekatain, S Schmitt, D Silver The 38th International Conference on Machine Learning, 2021 | 98 | 2021 |
Muesli: Combining Improvements in Policy Optimization M Hessel, I Danihelka, F Viola, A Guez, S Schmitt, L Sifre, T Weber, ... The 38th International Conference on Machine Learning, 2021 | 84 | 2021 |
Off-Policy Actor-Critic with Shared Experience Replay S Schmitt, M Hessel, K Simonyan The 37th International Conference on Machine Learning, 2020 | 58 | 2020 |
Gated linear networks J Veness, T Lattimore, D Budden, A Bhoopchand, C Mattern, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 10015 …, 2021 | 44 | 2021 |
Finding polynomial roots by dynamical systems -- A case study S Shemyakov, R Chernov, D Rumiantsau, D Schleicher, S Schmitt, ... Discrete & Continuous Dynamical Systems 40 (12), 6945-6965, 2020 | 10 | 2020 |
AlgebraNets J Hoffmann, S Schmitt, S Osindero, K Simonyan, E Elsen arXiv preprint arXiv:2006.07360, 2020 | 8 | 2020 |
Exploration via Epistemic Value Estimation S Schmitt, J Shawe-Taylor, H van Hasselt Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9742-9751, 2023 | 4 | 2023 |
Chaining Value Functions for Off-Policy Learning S Schmitt, J Shawe-Taylor, H van Hasselt Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8187-8195, 2022 | 1 | 2022 |