| Variational approaches for auto-encoding generative adversarial networks M Rosca, B Lakshminarayanan, D Warde-Farley, S Mohamed arXiv preprint arXiv:1706.04987, 2017 | 247 | 2017 |
| Monte Carlo Gradient Estimation in Machine Learning. S Mohamed, M Rosca, M Figurnov, A Mnih J. Mach. Learn. Res. 21 (132), 1-62, 2020 | 186 | 2020 |
| Many paths to equilibrium: GANs do not need to decrease a divergence at every step W Fedus, M Rosca, B Lakshminarayanan, AM Dai, S Mohamed, ... arXiv preprint arXiv:1710.08446, 2017 | 180 | 2017 |
| Deep compressed sensing Y Wu, M Rosca, T Lillicrap International Conference on Machine Learning, 6850-6860, 2019 | 100 | 2019 |
| Distribution matching in variational inference M Rosca, B Lakshminarayanan, S Mohamed arXiv preprint arXiv:1802.06847, 2018 | 77 | 2018 |
| Sequence-to-sequence neural network models for transliteration M Rosca, T Breuel arXiv preprint arXiv:1610.09565, 2016 | 48 | 2016 |
| Training language gans from scratch C de Masson d'Autume, S Mohamed, M Rosca, J Rae Advances in Neural Information Processing Systems 32, 2019 | 44 | 2019 |
| Learning implicit generative models with the method of learned moments S Ravuri, S Mohamed, M Rosca, O Vinyals International Conference on Machine Learning, 4314-4323, 2018 | 25 | 2018 |
| Optax: Composable gradient transformation and optimisation M Hessel, D Budden, F Viola, M Rosca, E Sezener, T Hennigan JAX, 2020 | 20 | 2020 |
| A case for new neural network smoothness constraints M Rosca, T Weber, A Gretton, S Mohamed PMLR, 2020 | 14 | 2020 |
| Optax: composable gradient transformation and optimisation, in jax!, 2020 M Hessel, D Budden, F Viola, M Rosca, E Sezener, T Hennigan URL http://github. com/deepmind/optax, 0 | 10 | |
| Spectral normalisation for deep reinforcement learning: an optimisation perspective F Gogianu, T Berariu, MC Rosca, C Clopath, L Busoniu, R Pascanu International Conference on Machine Learning, 3734-3744, 2021 | 7 | 2021 |
| Measure-valued derivatives for approximate bayesian inference M Rosca, M Figurnov, S Mohamed, A Mnih NeurIPS Workshop on Approximate Bayesian Inference, 2019 | 4 | 2019 |
| Networks with emotions: An investigation into deep belief nets and emotion recognition M Rosca Imperial College London, 2014 | 2* | 2014 |
| Discretization Drift in Two-Player Games MC Rosca, Y Wu, B Dherin, D Barrett International Conference on Machine Learning, 9064-9074, 2021 | 1 | 2021 |
| Compressed sensing using neural networks Y Wu, TP Lillicrap, M Rosca US Patent App. 16/818,895, 2020 | 1 | 2020 |
| Attractor neural networks for modelling associative memory W Al Jishi, N Hambuechen, R Marinescu, M Rosca, L Severyn January, 2013 | 1 | 2013 |
| Training language GANs from scratch M Rosca | | |
Shakir MohamedSenior Staff Scientist, DeepMindVahvistettu sähköpostiosoite verkkotunnuksessa deepmind.com
