Nicholas Watters

According to our database, Nicholas Watters authored at least 14 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task.

Jason Li, Nicholas Watters, Yingting Wang, Hansem Sohn, Mehrdad Jazayeri

CoRR, 2022

Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task.

Jason Li, Nicholas Watters, Hansem Sohn, Mehrdad Jazayeri

Proceedings of The 1st Gaze Meets ML workshop, 2022

2021

Modular Object-Oriented Games: A Task Framework for Reinforcement Learning, Psychology, and Neuroscience.

Nicholas Watters, Joshua B. Tenenbaum, Mehrdad Jazayeri

CoRR, 2021

2020

Unsupervised Model Selection for Variational Disentangled Representation Learning.

Sunny Duan, Loic Matthey, Andre Saraiva, Nick Watters, Chris Burgess, Alexander Lerchner, Irina Higgins

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning.

Sunny Duan, Nicholas Watters, Loic Matthey, Chris Burgess, Alexander Lerchner, Irina Higgins

CoRR, 2019

COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration.

Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P. Burgess, Alexander Lerchner

CoRR, 2019

MONet: Unsupervised Scene Decomposition and Representation.

Christopher P. Burgess, Loïc Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matthew M. Botvinick, Alexander Lerchner

CoRR, 2019

Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs.

Nicholas Watters, Loïc Matthey, Christopher P. Burgess, Alexander Lerchner

CoRR, 2019

Multi-Object Representation Learning with Iterative Variational Inference.

Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew M. Botvinick, Alexander Lerchner

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Understanding disentangling in β-VAE.

Christopher P. Burgess, Irina Higgins, Arka Pal, Loïc Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner

CoRR, 2018

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies.

Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher P. Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Visual Interaction Networks.

Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran

CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.

Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2014

Neuronal Spike Train Entropy Estimation by History Clustering.

Nicholas Watters, George N. Reeke

Neural Comput., 2014