Understanding disentangling in -VAE CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 2018 | 1114 | 2018 |
Monet: Unsupervised scene decomposition and representation CP Burgess, L Matthey, N Watters, R Kabra, I Higgins, M Botvinick, ... arXiv preprint arXiv:1901.11390, 2019 | 503 | 2019 |
Multi-object representation learning with iterative variational inference K Greff, RL Kaufman, R Kabra, N Watters, C Burgess, D Zoran, L Matthey, ... International conference on machine learning, 2424-2433, 2019 | 462 | 2019 |
Visual interaction networks: Learning a physics simulator from video N Watters, D Zoran, T Weber, P Battaglia, R Pascanu, A Tacchetti Advances in neural information processing systems 30, 2017 | 396 | 2017 |
Spatial broadcast decoder: A simple architecture for learning disentangled representations in vaes N Watters, L Matthey, CP Burgess, A Lerchner arXiv preprint arXiv:1901.07017, 2019 | 138 | 2019 |
Life-long disentangled representation learning with cross-domain latent homologies A Achille, T Eccles, L Matthey, C Burgess, N Watters, A Lerchner, ... Advances in Neural Information Processing Systems 31, 2018 | 134 | 2018 |
Cobra: Data-efficient model-based rl through unsupervised object discovery and curiosity-driven exploration N Watters, L Matthey, M Bosnjak, CP Burgess, A Lerchner arXiv preprint arXiv:1905.09275, 2019 | 120 | 2019 |
Unsupervised model selection for variational disentangled representation learning S Duan, L Matthey, A Saraiva, N Watters, CP Burgess, A Lerchner, ... arXiv preprint arXiv:1905.12614, 2019 | 79 | 2019 |
Understanding disentangling in β CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 2018 | 51 | 2018 |
Understanding disentangling in β-VAE. arXiv 2018 CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 1804 | 47 | 1804 |
Spriteworld: A Flexible, Configurable Reinforcement Learning Environment N Watters, L Matthey, S Borgeaud, R Kabra, A Lerchner https://github.com/deepmind/spriteworld, 2019 | 21 | 2019 |
Understanding disentangling in β-VAE. arXiv CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 2018 | 19 | 2018 |
Understanding disentangling in β β-VAE CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 2018 | 12 | 2018 |
Understanding disentangling in β-VAE. arXiv e-prints, page CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ... arXiv preprint arXiv:1804.03599, 2018 | 11 | 2018 |
Spatial broadcast decoder: A simple architecture for disentangled representations in vaes N Watters, L Matthey, CP Burgess, A Lerchner | 9 | 2019 |
Neuronal spike train entropy estimation by history clustering N Watters, GN Reeke Neural Computation 26 (9), 1840-1872, 2014 | 6 | 2014 |
Making object-level predictions of the future state of a physical system N Watters, R Pascanu, PW Battaglia, D Zorn, TG Weber US Patent 10,887,607, 2021 | 5 | 2021 |
Modular object-oriented games: a task framework for reinforcement learning, psychology, and neuroscience N Watters, J Tenenbaum, M Jazayeri arXiv preprint arXiv:2102.12616, 2021 | 4 | 2021 |
Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task J Li, N Watters, H Sohn, M Jazayeri Annual Conference on Neural Information Processing Systems, 98-112, 2023 | 2 | 2023 |
Computational basis of hierarchical and counterfactual information processing M Ramadan, C Tang, N Watters, M Jazayeri bioRxiv, 2024.01. 30.578076, 2024 | | 2024 |