| Imagination-augmented agents for deep reinforcement learning S Racanière, T Weber, D Reichert, L Buesing, A Guez, DJ Rezende, ... Advances in neural information processing systems, 5690-5701, 2017 | 600* | 2017 |
| Neural scene representation and rendering SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ... Science 360 (6394), 1204-1210, 2018 | 589 | 2018 |
| The predictron: End-to-end learning and planning D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ... Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 271 | 2017 |
| Relational Deep Reinforcement Learning V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... arXiv preprint arXiv:1806.01830, 2018 | 238 | 2018 |
| Deep reinforcement learning with relational inductive biases V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... International Conference on Learning Representations, 2018 | 166 | 2018 |
| Learning and Querying Fast Generative Models for Reinforcement Learning L Buesing, T Weber, S Racaniere, SM Eslami, D Rezende, DP Reichert, ... arXiv preprint arXiv:1802.03006, 2018 | 124 | 2018 |
| Learning model-based planning from scratch R Pascanu, Y Li, O Vinyals, N Heess, L Buesing, S Racanière, D Reichert, ... arXiv preprint arXiv:1707.06170, 2017 | 112 | 2017 |
| Neuronal Synchrony in Complex-Valued Deep Networks DP Reichert, T Serre arXiv preprint arXiv:1312.6115, 2013 | 92 | 2013 |
| Automated curricula through setter-solver interactions S Racaniere, AK Lampinen, A Santoro, DP Reichert, V Firoiu, TP Lillicrap arXiv preprint arXiv:1909.12892, 2019 | 70 | 2019 |
| Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex? DP Reichert, P Seriès, AJ Storkey PLOS Computational Biology 9 (7), e1003134, 2013 | 69 | 2013 |
| Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model DP Reichert, P Series, AJ Storkey Advances in Neural Information Processing Systems 23 (23), 2020-2028, 2010 | 60 | 2010 |
| A hierarchical generative model of recurrent object-based attention in the visual cortex DP Reichert, P Series, AJ Storkey International Conference on Artificial Neural Networks, 18-25, 2011 | 21 | 2011 |
| Alchemy: A structured task distribution for meta-reinforcement learning JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ... arXiv preprint arXiv:2102.02926, 2021 | 19 | 2021 |
| Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ... arXiv preprint arXiv:2102.02926, 2021 | 11 | 2021 |
| Neuronal adaptation for sampling-based probabilistic inference in perceptual bistability DP Reichert, P Seriès, AJ Storkey Advances in Neural Information Processing Systems, 2357-2365, 2011 | 8 | 2011 |
| Deep Boltzmann Machines as Hierarchical Generative Models of Perceptual Inference in the Cortex DP Reichert PhD thesis, University of Edinburgh, Edinburgh, UK, 2012 | 5 | 2012 |
| Imagination-based agent neural networks DP Wierstra, Y Li, R Pascanu, PW Battaglia, TG Weber, L Buesing, ... US Patent App. 16/689,058, 2020 | 2 | 2020 |
| Selectivity for non-accidental properties emerges from learning object transformation sequences S Parker, D Reichert, T Serre Journal of Vision 14 (10), 910-910, 2014 | 2 | 2014 |
| Imagination-based agent neural networks DP Wierstra, Y Li, R Pascanu, PW Battaglia, TG Weber, L Buesing, ... US Patent App. 16/689,017, 2020 | 1 | 2020 |
| Automated curriculum generation through setter-solver interactions S Racaniere, A Lampinen, A Santoro, D Reichert, V Firoiu, T Lillicrap International Conference on Learning Representations, 2019 | | 2019 |
Theophane WeberResearch Scientist at DeepMind在 google.com 的电子邮件经过验证
