Follow
Nicholas Watters
Title
Cited by
Cited by
Year
Understanding disentangling in -VAE
CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
10892018
Monet: Unsupervised scene decomposition and representation
CP Burgess, L Matthey, N Watters, R Kabra, I Higgins, M Botvinick, ...
arXiv preprint arXiv:1901.11390, 2019
4932019
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
4482019
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
3872017
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
1332019
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
1322018
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
1172019
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
752019
Understanding disentangling in β
CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
512018
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
461804
Spriteworld: A Flexible, Configurable Reinforcement Learning Environment
N Watters, L Matthey, S Borgeaud, R Kabra, A Lerchner
https://github.com/deepmind/spriteworld, 2019
212019
Understanding disentangling in β-VAE. arXiv
CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
192018
Understanding disentangling in β β-VAE
CP Burgess, I Higgins, A Pal, L Matthey, N Watters, G Desjardins, ...
arXiv preprint arXiv:1804.03599, 2018
122018
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
112018
Spatial broadcast decoder: A simple architecture for disentangled representations in vaes
N Watters, L Matthey, CP Burgess, A Lerchner
82019
Neuronal spike train entropy estimation by history clustering
N Watters, GN Reeke
Neural Computation 26 (9), 1840-1872, 2014
62014
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
52021
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
42021
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
22023
Computational basis of hierarchical and counterfactual information processing
M Ramadan, C Tang, N Watters, M Jazayeri
bioRxiv, 2024.01. 30.578076, 2024
2024
The system can't perform the operation now. Try again later.
Articles 1–20