Neil C. Rabinowitz

Publication Activity (10 Years)

Years Active: 2015-2022
Publications (10 Years): 28

Top Topics

Causal Structure

Reinforcement Learning

Intermediate Representations

Artificial Agents

Top Venues

Publications

Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane X. Wang, Andrea Banino, Felix Hill
Semantic Exploration from Language Abstractions and Pretrained Representations. CoRR (2022)
Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill
Semantic Exploration from Language Abstractions and Pretrained Representations. NeurIPS (2022)
Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz
Explainability Via Causal Self-Talk. CoRR (2022)
Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz
Explainability Via Causal Self-Talk. NeurIPS (2022)
Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie Cy Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill
Tell me why! Explanations support learning relational and causal structure. ICML (2022)
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
Tell me why! - Explanations support learning of relational and causal structure. CoRR (2021)
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
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. NeurIPS Datasets and Benchmarks (2021)
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 Botvinick
Alchemy: A structured task distribution for meta-reinforcement learning. CoRR (2021)
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
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR (2020)
János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti
Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions. COIN(E)@AAMAS (2020)
János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti
Should I tear down this wall? Optimizing social metrics by evaluating novel actions. CoRR (2020)
Neil C. Rabinowitz
Meta-learners' learning dynamics are unlike learners'. CoRR (2019)
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew Botvinick, Peter W. Battaglia
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) (2019)
Tom Le Paine, Çaglar Gülçehre, 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
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR (2019)
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 Botvinick, Shane Legg
Meta-learning of Sequential Strategies. CoRR (2019)
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
Vector-based navigation using grid-like representations in artificial agents. Nat. 557 (7705) (2018)
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew Botvinick, Peter W. Battaglia
Relational Forward Models for Multi-Agent Learning. CoRR (2018)
Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick
Machine Theory of Mind. ICML (2018)
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew Botvinick
On the importance of single directions for generalization. ICLR (Poster) (2018)
Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos, Daniel Zoran
Learned Deformation Stability in Convolutional Neural Networks. CoRR (2018)
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew Botvinick
On the importance of single directions for generalization. CoRR (2018)
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
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR (2018)
Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick
Machine Theory of Mind. CoRR (2018)
Matthew 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
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR (2017)
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
The Predictron: End-To-End Learning and Planning. ICML (2017)
Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, Raia Hadsell
Progressive Neural Networks. CoRR (2016)
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
The Predictron: End-To-End Learning and Planning. CoRR (2016)
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
Overcoming catastrophic forgetting in neural networks. CoRR (2016)
Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli
The local low-dimensionality of natural images. ICLR (2015)