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Nicholas Watters
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- affiliation: DeepMind, London, UK
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Journal Articles
- 2014
- [j1]Nicholas Watters, George N. Reeke:
Neuronal Spike Train Entropy Estimation by History Clustering. Neural Comput. 26(9): 1840-1872 (2014)
Conference and Workshop Papers
- 2022
- [c5]Jason Li, Nicholas Watters, Hansem Sohn, Mehrdad Jazayeri:
Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task. Gaze Meets ML 2022: 98-112 - 2020
- [c4]Sunny Duan, Loic Matthey, Andre Saraiva, Nick Watters, Chris Burgess, Alexander Lerchner, Irina Higgins:
Unsupervised Model Selection for Variational Disentangled Representation Learning. ICLR 2020 - 2019
- [c3]Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew M. Botvinick, Alexander Lerchner:
Multi-Object Representation Learning with Iterative Variational Inference. ICML 2019: 2424-2433 - 2018
- [c2]Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher P. Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins:
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. NeurIPS 2018: 9895-9905 - 2017
- [c1]Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti:
Visual Interaction Networks: Learning a Physics Simulator from Video. NIPS 2017: 4539-4547
Informal and Other Publications
- 2022
- [i10]Jason Li, Nicholas Watters, Yingting Wang, Hansem Sohn, Mehrdad Jazayeri:
Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task. CoRR abs/2212.10367 (2022) - 2021
- [i9]Nicholas Watters, Joshua B. Tenenbaum, Mehrdad Jazayeri:
Modular Object-Oriented Games: A Task Framework for Reinforcement Learning, Psychology, and Neuroscience. CoRR abs/2102.12616 (2021) - 2019
- [i8]Nicholas Watters, Loïc Matthey, Christopher P. Burgess, Alexander Lerchner:
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs. CoRR abs/1901.07017 (2019) - [i7]Christopher P. Burgess, Loïc Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matthew M. Botvinick, Alexander Lerchner:
MONet: Unsupervised Scene Decomposition and Representation. CoRR abs/1901.11390 (2019) - [i6]Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loïc Matthey, Matthew M. Botvinick, Alexander Lerchner
:
Multi-Object Representation Learning with Iterative Variational Inference. CoRR abs/1903.00450 (2019) - [i5]Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P. Burgess, Alexander Lerchner:
COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration. CoRR abs/1905.09275 (2019) - [i4]Sunny Duan, Nicholas Watters, Loic Matthey, Chris Burgess, Alexander Lerchner, Irina Higgins:
A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning. CoRR abs/1905.12614 (2019) - 2018
- [i3]Christopher P. Burgess, Irina Higgins, Arka Pal, Loïc Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner:
Understanding disentangling in β-VAE. CoRR abs/1804.03599 (2018) - [i2]Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher P. Burgess, Nick Watters, Alexander Lerchner, Irina Higgins:
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. CoRR abs/1808.06508 (2018) - 2017
- [i1]Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran:
Visual Interaction Networks. CoRR abs/1706.01433 (2017)
Coauthor Index
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