| Stochastic backpropagation and approximate inference in deep generative models DJ Rezende, S Mohamed, D Wierstra International conference on machine learning, 1278-1286, 2014 | 6971 | 2014 |
| Variational inference with normalizing flows D Rezende, S Mohamed International conference on machine learning, 1530-1538, 2015 | 5994 | 2015 |
| Semi-supervised learning with deep generative models DP Kingma, DJ Rezende, S Mohamed, M Welling Advances in neural information processing systems 27, 2014 | 4076 | 2014 |
| Normalizing flows for probabilistic modeling and inference G Papamakarios, E Nalisnick, DJ Rezende, S Mohamed, ... Journal of Machine Learning Research 22 (57), 1-64, 2021 | 2728 | 2021 |
| Draw: A recurrent neural network for image generation K Gregor, I Danihelka, A Graves, D Rezende, D Wierstra International conference on machine learning, 1462-1471, 2015 | 2696 | 2015 |
| Interaction networks for learning about objects, relations and physics P Battaglia, R Pascanu, M Lai, D Jimenez Rezende Advances in neural information processing systems 29, 2016 | 1949 | 2016 |
| Conditional neural processes M Garnelo, D Rosenbaum, C Maddison, T Ramalho, D Saxton, ... International conference on machine learning, 1704-1713, 2018 | 1005 | 2018 |
| Neural scene representation and rendering SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ... Science 360 (6394), 1204-1210, 2018 | 817 | 2018 |
| Imagination-augmented agents for deep reinforcement learning S Racanière, T Weber, D Reichert, L Buesing, A Guez, ... Advances in neural information processing systems 30, 2017 | 811 | 2017 |
| 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 | 802 | 2018 |
| Neural processes M Garnelo, J Schwarz, D Rosenbaum, F Viola, DJ Rezende, SM Eslami, ... arXiv preprint arXiv:1807.01622, 2018 | 792 | 2018 |
| Towards a definition of disentangled representations I Higgins, D Amos, D Pfau, S Racaniere, L Matthey, D Rezende, ... arXiv preprint arXiv:1812.02230, 2018 | 701 | 2018 |
| Variational intrinsic control K Gregor, DJ Rezende, D Wierstra arXiv preprint arXiv:1611.07507, 2016 | 562 | 2016 |
| Variational information maximisation for intrinsically motivated reinforcement learning S Mohamed, D Jimenez Rezende Advances in neural information processing systems 28, 2015 | 528 | 2015 |
| 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 | 476 | 2016 |
| Variational inference for monte carlo objectives A Mnih, D Rezende International Conference on Machine Learning, 2188-2196, 2016 | 379 | 2016 |
| One-shot generalization in deep generative models D Rezende, I Danihelka, K Gregor, D Wierstra International conference on machine learning, 1521-1529, 2016 | 326 | 2016 |
| Towards conceptual compression K Gregor, F Besse, D Jimenez Rezende, I Danihelka, D Wierstra Advances in neural information processing systems 29, 2016 | 305 | 2016 |
| Equivariant flow-based sampling for lattice gauge theory G Kanwar, MS Albergo, D Boyda, K Cranmer, DC Hackett, S Racaniere, ... Physical Review Letters 125 (12), 121601, 2020 | 304 | 2020 |
| Hamiltonian generative networks P Toth, DJ Rezende, A Jaegle, S Racanière, A Botev, I Higgins arXiv preprint arXiv:1909.13789, 2019 | 290 | 2019 |
Shakir MohamedResearch Director, Google DeepMindVerified email at deepmind.com
