Neil C. Rabinowitz

According to our database, Neil C. Rabinowitz authored at least 21 papers between 2015 and 2022.

Collaborative distances:

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

2022

Semantic Exploration from Language Abstractions and Pretrained Representations.

Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Explainability Via Causal Self-Talk.

Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Tell me why! Explanations support learning relational and causal structure.

Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill

Proceedings of the International Conference on Machine Learning, 2022

2021

Alchemy: A structured task distribution for meta-reinforcement learning.

Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew M. Botvinick

CoRR, 2021

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents.

Jane Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charles Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matt M. Botvinick

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems.

Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team

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

Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions.

János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti

Proceedings of the Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII, 2020

2019

Meta-learning of Sequential Strategies.

Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg

CoRR, 2019

Meta-learners' learning dynamics are unlike learners'.

Neil C. Rabinowitz

CoRR, 2019

Relational Forward Models for Multi-Agent Learning.

Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Vector-based navigation using grid-like representations in artificial agents.

Andrea Banino, Caswell Barry, Benigno Uria, Charles Blundell, Timothy P. Lillicrap, Piotr Mirowski, Alexander Pritzel, Martin J. Chadwick, Thomas Degris, Joseph Modayil, Greg Wayne, Hubert Soyer, Fabio Viola, Brian Zhang, Ross Goroshin, Neil C. Rabinowitz, Razvan Pascanu, Charlie Beattie, Stig Petersen, Amir Sadik, Stephen Gaffney, Helen King, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Dharshan Kumaran

Nat., 2018

Relational Forward Models for Multi-Agent Learning.

Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia

CoRR, 2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.

Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel

CoRR, 2018

Learned Deformation Stability in Convolutional Neural Networks.

Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos, Daniel Zoran

CoRR, 2018

Machine Theory of Mind.

Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick

Proceedings of the 35th International Conference on Machine Learning, 2018

On the importance of single directions for generalization.

Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.

Matthew M. Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis

CoRR, 2017

The Predictron: End-To-End Learning and Planning.

David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Progressive Neural Networks.

Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, Raia Hadsell

CoRR, 2016

Overcoming catastrophic forgetting in neural networks.

James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell

CoRR, 2016

2015

The local low-dimensionality of natural images.

Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli

Proceedings of the 3rd International Conference on Learning Representations, 2015