| The Pascal Visual Object Classes Challenge–a Retrospective M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ... IJCV, 2014 | 5512 | 2014 |
| 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 | 1072 | 2020 |
| 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 | 893 | 2017 |
| Neural scene representation and rendering SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ... Science 360 (6394), 1204-1210, 2018 | 566 | 2018 |
| Conditional neural processes M Garnelo, D Rosenbaum, C Maddison, T Ramalho, D Saxton, ... International conference on machine learning, 1704-1713, 2018 | 507 | 2018 |
| 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 | 496 | 2016 |
| 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 31, 2018 | 408 | 2018 |
| Neural processes M Garnelo, J Schwarz, D Rosenbaum, F Viola, DJ Rezende, SM Eslami, ... arXiv preprint arXiv:1807.01622, 2018 | 404 | 2018 |
| Machine theory of mind N Rabinowitz, F Perbet, F Song, C Zhang, SMA Eslami, M Botvinick International conference on machine learning, 4218-4227, 2018 | 399 | 2018 |
| 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, 2016 | 395 | 2016 |
| Attentive neural processes H Kim, A Mnih, J Schwarz, M Garnelo, A Eslami, D Rosenbaum, O Vinyals, ... arXiv preprint arXiv:1901.05761, 2019 | 289 | 2019 |
| The shape boltzmann machine: a strong model of object shape SMA Eslami, N Heess, CKI Williams, J Winn International Journal of Computer Vision 107, 155-176, 2014 | 253 | 2014 |
| 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 | 253 | 2014 |
| Synthesizing programs for images using reinforced adversarial learning Y Ganin, T Kulkarni, I Babuschkin, SMA Eslami, O Vinyals International Conference on Machine Learning, 1666-1675, 2018 | 194 | 2018 |
| Multimodal few-shot learning with frozen language models M Tsimpoukelli, JL Menick, S Cabi, SM Eslami, O Vinyals, F Hill Advances in Neural Information Processing Systems 34, 200-212, 2021 | 169 | 2021 |
| Contrastive training for improved out-of-distribution detection J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ... arXiv preprint arXiv:2007.05566, 2020 | 142 | 2020 |
| Polygen: An autoregressive generative model of 3d meshes C Nash, Y Ganin, SMA Eslami, P Battaglia International conference on machine learning, 7220-7229, 2020 | 110 | 2020 |
| Kickstarting deep reinforcement learning S Schmitt, JJ Hudson, A Zidek, S Osindero, C Doersch, WM Czarnecki, ... arXiv preprint arXiv:1803.03835, 2018 | 101 | 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 | 98 | 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 | 85 | 2017 |
Danilo J. RezendeSenior Staff Research Scientist at DeepMindAdresse e-mail validée de google.com
