| The Pascal Visual Object Classes Challenge–a Retrospective M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ... IJCV, 2014 | 2994 | 2014 |
| Emergence of locomotion behaviours in rich environments N Heess, D TB, S Sriram, J Lemmon, J Merel, G Wayne, Y Tassa, T Erez, ... arXiv preprint arXiv:1707.02286, 2017 | 484 | 2017 |
| Attend, infer, repeat: Fast scene understanding with generative models SMA Eslami, N Heess, T Weber, Y Tassa, D Szepesvari, GE Hinton Advances in Neural Information Processing Systems, 3225-3233, 2016 | 286 | 2016 |
| Unsupervised learning of 3d structure from images D Jimenez Rezende, SM Eslami, S Mohamed, P Battaglia, M Jaderberg, ... Advances in neural information processing systems 29, 4996-5004, 2016 | 280 | 2016 |
| Neural scene representation and rendering SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ... Science 360 (6394), 1204-1210, 2018 | 277 | 2018 |
| Data-efficient image recognition with contrastive predictive coding OJ Hénaff, A Srinivas, J De Fauw, A Razavi, C Doersch, SMA Eslami, ... International Conference on Machine Learning, 4182-4192, 2020 | 254 | 2020 |
| The Shape Boltzmann Machine: a Strong Model of Object Shape SMA Eslami, N Heess, CKI Williams, J Winn International Journal of Computer Vision 107 (2), 155-176, 2014 | 216 | 2014 |
| Conditional neural processes M Garnelo, D Rosenbaum, CJ Maddison, T Ramalho, D Saxton, ... arXiv preprint arXiv:1807.01613, 2018 | 186 | 2018 |
| Neural processes M Garnelo, J Schwarz, D Rosenbaum, F Viola, DJ Rezende, SM Eslami, ... arXiv preprint arXiv:1807.01622, 2018 | 158 | 2018 |
| Machine theory of mind NC Rabinowitz, F Perbet, HF Song, C Zhang, SM Eslami, M Botvinick arXiv preprint arXiv:1802.07740, 2018 | 158 | 2018 |
| A probabilistic u-net for segmentation of ambiguous images S Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ... Advances in neural information processing systems, 6965-6975, 2018 | 153 | 2018 |
| Synthesizing programs for images using reinforced adversarial learning Y Ganin, T Kulkarni, I Babuschkin, SM Eslami, O Vinyals arXiv preprint arXiv:1804.01118, 2018 | 105 | 2018 |
| Attentive neural processes H Kim, A Mnih, J Schwarz, M Garnelo, A Eslami, D Rosenbaum, O Vinyals, ... arXiv preprint arXiv:1901.05761, 2019 | 88 | 2019 |
| A Generative Model for Parts-based Object Segmentation SMA Eslami, CKI Williams Neural Information Processing Systems, 2012 | 67 | 2012 |
| 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 | 58 | 2018 |
| Few-shot autoregressive density estimation: Towards learning to learn distributions S Reed, Y Chen, T Paine, A Oord, SM Eslami, D Rezende, O Vinyals, ... arXiv preprint arXiv:1710.10304, 2017 | 51 | 2017 |
| Kickstarting deep reinforcement learning S Schmitt, JJ Hudson, A Zidek, S Osindero, C Doersch, WM Czarnecki, ... arXiv preprint arXiv:1803.03835, 2018 | 45 | 2018 |
| Kernel-based just-in-time learning for passing expectation propagation messages W Jitkrittum, A Gretton, N Heess, SM Eslami, B Lakshminarayanan, ... arXiv preprint arXiv:1503.02551, 2015 | 30 | 2015 |
| Van Gool, L M Everingham Williams, CKI, Winn, J. and Zisserman, A. The PASCAL Visual Object Classes …, 2012 | 25 | 2012 |
| Consistent generative query networks A Kumar, SM Eslami, DJ Rezende, M Garnelo, F Viola, E Lockhart, ... arXiv preprint arXiv:1807.02033, 2018 | 21 | 2018 |
John WinnPrincipal Researcher, Machine Learning Group, Microsoft Research CambridgeVerified email at microsoft.com
