| Neural scene representation and rendering SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ... Science 360 (6394), 1204-1210, 2018 | 722 | 2018 |
| Towards conceptual compression K Gregor, F Besse, D Jimenez Rezende, I Danihelka, D Wierstra Advances in neural information processing systems 29, 2016 | 326* | 2016 |
| Pmbp: Patchmatch belief propagation for correspondence field estimation F Besse, C Rother, A Fitzgibbon, J Kautz International Journal of Computer Vision 110, 2-13, 2014 | 282 | 2014 |
| Temporal difference variational auto-encoder K Gregor, G Papamakarios, F Besse, L Buesing, T Weber arXiv preprint arXiv:1806.03107, 2018 | 149 | 2018 |
| Convolution by evolution: Differentiable pattern producing networks C Fernando, D Banarse, M Reynolds, F Besse, D Pfau, M Jaderberg, ... Proceedings of the Genetic and Evolutionary Computation Conference 2016, 109-116, 2016 | 136 | 2016 |
| Shaping belief states with generative environment models for rl K Gregor, D Jimenez Rezende, F Besse, Y Wu, H Merzic, A van den Oord Advances in Neural Information Processing Systems 32, 2019 | 115 | 2019 |
| 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 | 112 | 2018 |
| Highly overparameterized optical flow using patchmatch belief propagation M Hornáček, F Besse, J Kautz, A Fitzgibbon, C Rother Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 43 | 2014 |
| Causally correct partial models for reinforcement learning DJ Rezende, I Danihelka, G Papamakarios, NR Ke, R Jiang, T Weber, ... arXiv preprint arXiv:2002.02836, 2020 | 34 | 2020 |
| Learning models for visual 3d localization with implicit mapping D Rosenbaum, F Besse, F Viola, DJ Rezende, SM Eslami arXiv preprint arXiv:1807.03149, 2018 | 34 | 2018 |
| Demis Hassabis, et al. 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 2, 2018 | 34 | 2018 |
| TF-Replicator: Distributed machine learning for researchers P Buchlovsky, D Budden, D Grewe, C Jones, J Aslanides, F Besse, ... arXiv preprint arXiv:1902.00465, 2019 | 24 | 2019 |
| Encoding spatial relations from natural language T Ramalho, T Kočiský, F Besse, SM Eslami, G Melis, F Viola, P Blunsom, ... arXiv preprint arXiv:1807.01670, 2018 | 14 | 2018 |
| Self-organizing intelligent matter: A blueprint for an ai generating algorithm K Gregor, F Besse arXiv preprint arXiv:2101.07627, 2021 | 11 | 2021 |
| PatchMatch Belief Propagation for Correspondence Field Estimation and Its Applications FO Besse UCL (University College London), 2013 | 7 | 2013 |
| Scaling Instructable Agents Across Many Simulated Worlds MA Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, B Brownfield, ... arXiv preprint arXiv:2404.10179, 2024 | 6 | 2024 |
| Scaling instructable agents across many simulated worlds M Abi Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, B Brownfield, ... arXiv e-prints, arXiv: 2404.10179, 2024 | 4 | 2024 |
| Learning to encode spatial relations from natural language T Ramalho, T Kocisky, F Besse, SMA Eslami, G Melis, F Viola, P Blunsom, ... | 3 | 2018 |
| Scene understanding and generation using neural networks DJ Rezende, SM Eslami, K Gregor, FO Besse US Patent App. 18/164,021, 2023 | | 2023 |
| Scene understanding and generation using neural networks DJ Rezende, SM Eslami, K Gregor, FO Besse US Patent 11,587,344, 2023 | | 2023 |
