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 | 4896 | 2019 |
Scaling language models: Methods, analysis & insights from training gopher JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ... arXiv preprint arXiv:2112.11446, 2021 | 1062 | 2021 |
Full-resolution residual networks for semantic segmentation in street scenes T Pohlen, A Hermans, M Mathias, B Leibe Computer Vision and Pattern Recognition (CVPR), 2017 | 711 | 2017 |
Reward learning from human preferences and demonstrations in Atari B Ibarz, J Leike, T Pohlen, G Irving, S Legg, D Amodei Advances in Neural Information Processing Systems (NIPS/NeurIPS), 2018 | 430 | 2018 |
Mastering the game of Stratego with model-free multiagent reinforcement learning J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ... Science 378 (6623), 990-996, 2022 | 218 | 2022 |
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 | 143 | 2018 |
A data-driven approach for learning to control computers PC Humphreys, D Raposo, T Pohlen, G Thornton, R Chhaparia, A Muldal, ... International Conference on Machine Learning, 9466-9482, 2022 | 102 | 2022 |
Semantic segmentation of modular furniture T Pohlen, I Badami, M Mathias, B Leibe Applications of Computer Vision (WACV), 2016 | 10 | 2016 |
Learned computer control using pointing device and keyboard actions PC Humphreys, TP Lillicrap, TM Pohlen, AA Santoro US Patent App. 18/103,309, 2023 | | 2023 |
Towards Consistent Performance on Atari using Expert Demonstrations T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ... | | |