| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... Nature 575 (7782), 350-354, 2019 | 4115 | 2019 |
| Starcraft ii: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 1009 | 2017 |
| Magnetic control of tokamak plasmas through deep reinforcement learning J Degrave, F Felici, J Buchli, M Neunert, B Tracey, F Carpanese, T Ewalds, ... Nature 602 (7897), 414-419, 2022 | 606 | 2022 |
| Alphastar: Mastering the real-time strategy game starcraft ii O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ... DeepMind blog 2, 20, 2019 | 540 | 2019 |
| Improving alignment of dialogue agents via targeted human judgements A Glaese, N McAleese, M Trębacz, J Aslanides, V Firoiu, T Ewalds, ... arXiv preprint arXiv:2209.14375, 2022 | 286 | 2022 |
| OpenSpiel: A framework for reinforcement learning in games M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ... arXiv preprint arXiv:1908.09453, 2019 | 229 | 2019 |
| GraphCast: Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... arXiv preprint arXiv:2212.12794, 2022 | 164 | 2022 |
| Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... Science 382 (6677), 1416-1421, 2023 | 105 | 2023 |
| Guidelines for quantitative reconstruction of complex exit waves in HRTEM C Ophus, T Ewalds Ultramicroscopy 113, 88-95, 2012 | 36 | 2012 |
| Starcraft ii unplugged: Large scale offline reinforcement learning M Mathieu, S Ozair, S Srinivasan, C Gulcehre, S Zhang, R Jiang, ... Deep RL Workshop NeurIPS 2021, 2021 | 16 | 2021 |
| Playing and solving Havannah TV Ewalds | 16 | 2012 |
| The role of self-shadowing on growth and scaling laws of faceted polycrystalline thin films C Ophus, T Ewalds, EJ Luber, D Mitlin Acta materialia 58 (15), 5150-5159, 2010 | 14 | 2010 |
| Gencast: Diffusion-based ensemble forecasting for medium-range weather I Price, A Sanchez-Gonzalez, F Alet, T Ewalds, A El-Kadi, J Stott, ... arXiv preprint arXiv:2312.15796, 2023 | 12 | 2023 |
| & Quan, J.(2017). Starcraft ii: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo arXiv preprint arXiv:1708.04782, 0 | 7 | |
| AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning M Mathieu, S Ozair, S Srinivasan, C Gulcehre, S Zhang, R Jiang, ... arXiv preprint arXiv:2308.03526, 2023 | 3 | 2023 |
| Towards practical reinforcement learning for tokamak magnetic control BD Tracey, A Michi, Y Chervonyi, I Davies, C Paduraru, N Lazic, F Felici, ... arXiv preprint arXiv:2307.11546, 2023 | 2 | 2023 |
| Towards practical reinforcement learning for tokamak magnetic control BD Tracey, A Michi, Y Chervonyi, I Davies, C Paduraru, N Lazic, F Felici, ... Fusion Engineering and Design 200, 114161, 2024 | 1 | 2024 |
| X-point radiator and power exhaust control in configurations with multiple X-points in TCV S Gorno, O Fevrier, C Theiler, C Colandrea, F Bagnato, J Degrave, ... APS Division of Plasma Physics Meeting Abstracts 2023, BI02. 002, 2023 | | 2023 |
Petko GeorgievGoogle DeepMind, University of CambridgeVerifierad e-postadress på cam.ac.uk
