| Virel: A variational inference framework for reinforcement learning M Fellows, A Mahajan, TGJ Rudner, S Whiteson Advances in neural information processing systems 32, 2019 | 63 | 2019 |
| Bayesian bellman operators M Fellows, K Hartikainen, S Whiteson Advances in Neural Information Processing Systems 34, 13641-13656, 2021 | 21 | 2021 |
| Fourier policy gradients M Fellows, K Ciosek, S Whiteson International Conference on Machine Learning, 1486-1495, 2018 | 16 | 2018 |
| Simplifying deep temporal difference learning M Gallici, M Fellows, B Ellis, B Pou, I Masmitja, JN Foerster, M Martin arXiv preprint arXiv:2407.04811, 2024 | 11 | 2024 |
| Why target networks stabilise temporal difference methods M Fellows, MJA Smith, S Whiteson International Conference on Machine Learning, 9886-9909, 2023 | 8 | 2023 |
| Refining Minimax Regret for Unsupervised Environment Design M Beukman, S Coward, M Matthews, M Fellows, M Jiang, M Dennis, ... arXiv preprint arXiv:2402.12284, 2024 | 7 | 2024 |
| Bayesian Exploration Networks M Fellows, B Kaplowitz, CS de Witt, S Whiteson arXiv preprint arXiv:2308.13049, 2023 | 1 | 2023 |
| Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps B Ellis, MT Jackson, A Lupu, AD Goldie, M Fellows, S Whiteson, ... arXiv preprint arXiv:2412.17113, 2024 | | 2024 |
| A Bayesian Solution To The Imitation Gap R Vuorio, M Fellows, C Lu, C Grislain, S Whiteson arXiv preprint arXiv:2407.00495, 2024 | | 2024 |
| Bayesian and variational inference for reinforcement learning M Fellows University of Oxford, 2021 | | 2021 |
