| What about inputting policy in value function: Policy representation and policy-extended value function approximator H Tang, Z Meng, J Hao, C Chen, D Graves, D Li, C Yu, H Mao, W Liu, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8441-8449, 2022 | 20* | 2022 |
| Deep kernel learning approach to engine emissions modeling C Yu, M Seslija, G Brownbridge, S Mosbach, M Kraft, M Parsi, M Davis, ... Data-Centric Engineering 1, 2020 | 18 | 2020 |
| Learning State Representations via Retracing in Reinforcement Learning C Yu, D Li, J Hao, J Wang, N Burgess arXiv preprint arXiv:2111.12600, 2021 | 9 | 2021 |
| Prediction and Generalisation over Directed Actions by Grid Cells C Yu, TEJ Behrens, N Burgess arXiv preprint arXiv:2006.03355, 2020 | 6* | 2020 |
| DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention D Mguni, J Jennings, T Jafferjee, A Sootla, Y Yang, C Yu, U Islam, Z Wang, ... arXiv preprint arXiv:2110.14468, 2021 | 5 | 2021 |
| Structured Recognition for Generative Models with Explaining Away C Yu, H Soulat, N Burgess, M Sahani Advances in Neural Information Processing Systems, 2022 | 4* | 2022 |
| Unsupervised representation learning with recognition-parametrised probabilistic models WI Walker, H Soulat, C Yu, M Sahani International Conference on Artificial Intelligence and Statistics, 4209-4230, 2023 | 2 | 2023 |
| Successor-Predecessor Intrinsic Exploration C Yu, N Burgess, M Sahani, SJ Gershman Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| SEREN: Knowing When to Explore and When to Exploit C Yu, D Mguni, D Li, A Sootla, J Wang, N Burgess arXiv preprint arXiv:2205.15064, 2022 | 1 | 2022 |
| Leveraging Episodic Memory to Improve World Models for Reinforcement Learning J Coda-Forno, C Yu, Q Guo, Z Fountas, N Burgess | | |
Neil BurgessProfessor of Cognitive Neuroscience, University College London在 ucl.ac.uk 的电子邮件经过验证
