| Generalization in reinforcement learning with selective noise injection and information bottleneck M Igl, K Ciosek, Y Li, S Tschiatschek, C Zhang, S Devlin, K Hofmann Advances in neural information processing systems 32, 2019 | 186 | 2019 |
| Better exploration with optimistic actor critic K Ciosek, Q Vuong, R Loftin, K Hofmann Advances in Neural Information Processing Systems 32, 2019 | 167 | 2019 |
| Expected policy gradients K Ciosek, S Whiteson Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 87 | 2018 |
| Discount factor as a regularizer in reinforcement learning R Amit, R Meir, K Ciosek International conference on machine learning, 269-278, 2020 | 80 | 2020 |
| Compositional planning using optimal option models D Silver, K Ciosek arXiv preprint arXiv:1206.6473, 2012 | 69 | 2012 |
| Conservative uncertainty estimation by fitting prior networks K Ciosek, V Fortuin, R Tomioka, K Hofmann, R Turner International Conference on Learning Representations, 2019 | 68 | 2019 |
| Offer: Off-environment reinforcement learning K Ciosek, S Whiteson Proceedings of the aaai conference on artificial intelligence 31 (1), 2017 | 61 | 2017 |
| Expected policy gradients for reinforcement learning K Ciosek, S Whiteson Journal of Machine Learning Research 21 (52), 1-51, 2020 | 52 | 2020 |
| Multi-task batch reinforcement learning with metric learning J Li, Q Vuong, S Liu, M Liu, K Ciosek, H Christensen, H Su Advances in neural information processing systems 33, 6197-6210, 2020 | 50 | 2020 |
| Deep interactive bayesian reinforcement learning via meta-learning L Zintgraf, S Devlin, K Ciosek, S Whiteson, K Hofmann arXiv preprint arXiv:2101.03864, 2021 | 38 | 2021 |
| Evaluating the robustness of collaborative agents P Knott, M Carroll, S Devlin, K Ciosek, K Hofmann, AD Dragan, R Shah arXiv preprint arXiv:2101.05507, 2021 | 29 | 2021 |
| Imitation learning by reinforcement learning K Ciosek arXiv preprint arXiv:2108.04763, 2021 | 24 | 2021 |
| Alternating optimisation and quadrature for robust control S Paul, K Chatzilygeroudis, K Ciosek, JB Mouret, M Osborne, S Whiteson Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 23 | 2018 |
| Amrl: Aggregated memory for reinforcement learning J Beck, K Ciosek, S Devlin, S Tschiatschek, C Zhang, K Hofmann International Conference on Learning Representations, 2020 | 22 | 2020 |
| Information directed reward learning for reinforcement learning D Lindner, M Turchetta, S Tschiatschek, K Ciosek, A Krause Advances in Neural Information Processing Systems 34, 3850-3862, 2021 | 18 | 2021 |
| Regularized policies are reward robust H Husain, K Ciosek, R Tomioka International Conference on Artificial Intelligence and Statistics, 64-72, 2021 | 17 | 2021 |
| Drift: Deep reinforcement learning for functional software testing L Harries, RS Clarke, T Chapman, SV Nallamalli, L Ozgur, S Jain, ... arXiv preprint arXiv:2007.08220, 2020 | 16 | 2020 |
| Fourier policy gradients M Fellows, K Ciosek, S Whiteson International Conference on Machine Learning, 1486-1495, 2018 | 16 | 2018 |
| Value iteration with options and state aggregation K Ciosek, D Silver arXiv preprint arXiv:1501.03959, 2015 | 15 | 2015 |
| Impatient bandits: Optimizing recommendations for the long-term without delay TM McDonald, L Maystre, M Lalmas, D Russo, K Ciosek Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 13 | 2023 |
