| The Pascal Visual Object Classes Challenge–a Retrospective M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ... IJCV, 2014 | 11329 | 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 | 1595 | 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 | 1143 | 2017 |
| Conditional neural processes M Garnelo, D Rosenbaum, C Maddison, T Ramalho, D Saxton, ... International conference on machine learning, 1704-1713, 2018 | 785 | 2018 |
| Neural scene representation and rendering SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ... Science 360 (6394), 1204-1210, 2018 | 722 | 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 | 676 | 2021 |
| Neural processes M Garnelo, J Schwarz, D Rosenbaum, F Viola, DJ Rezende, SM Eslami, ... arXiv preprint arXiv:1807.01622, 2018 | 627 | 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 | 620 | 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 31, 2018 | 613 | 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 | 598 | 2016 |
| Attentive neural processes H Kim, A Mnih, J Schwarz, M Garnelo, A Eslami, D Rosenbaum, O Vinyals, ... arXiv preprint arXiv:1901.05761, 2019 | 463 | 2019 |
| 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 | 454 | 2016 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 394 | 2024 |
| 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 | 267 | 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 | 250 | 2018 |
| 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 | 247 | 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 | 246 | 2020 |
| From data to functa: Your data point is a function and you can treat it like one E Dupont, H Kim, SM Eslami, D Rezende, D Rosenbaum arXiv preprint arXiv:2201.12204, 2022 | 164 | 2022 |
| Kickstarting deep reinforcement learning S Schmitt, JJ Hudson, A Zidek, S Osindero, C Doersch, WM Czarnecki, ... arXiv preprint arXiv:1803.03835, 2018 | 148 | 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 | 142 | 2018 |
Danilo J. RezendeDirector at DeepMind在 google.com 的电子邮件经过验证
