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Neil C. Rabinowitz
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2020 – today
- 2022
- [c11]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 relational and causal structure. ICML 2022: 11868-11890 - [c10]Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz:
Explainability Via Causal Self-Talk. NeurIPS 2022 - [c9]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 - [i17]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 abs/2204.05080 (2022) - [i16]Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz:
Explainability Via Causal Self-Talk. CoRR abs/2211.09937 (2022) - 2021
- [c8]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 - [i15]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:
Alchemy: A structured task distribution for meta-reinforcement learning. CoRR abs/2102.02926 (2021) - [i14]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 abs/2112.03753 (2021) - 2020
- [c7]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: 114-130 - [c6]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 - [i13]János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti:
Should I tear down this wall? Optimizing social metrics by evaluating novel actions. CoRR abs/2004.07625 (2020)
2010 – 2019
- 2019
- [c5]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:
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) 2019 - [i12]Neil C. Rabinowitz:
Meta-learners' learning dynamics are unlike learners'. CoRR abs/1905.01320 (2019) - [i11]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:
Meta-learning of Sequential Strategies. CoRR abs/1905.03030 (2019) - [i10]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 abs/1909.01387 (2019) - 2018
- [j1]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
Vector-based navigation using grid-like representations in artificial agents. Nat. 557(7705): 429-433 (2018) - [c4]Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick:
On the importance of single directions for generalization. ICLR (Poster) 2018 - [c3]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. ICML 2018: 4215-4224 - [i9]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. CoRR abs/1802.07740 (2018) - [i8]Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick:
On the importance of single directions for generalization. CoRR abs/1803.06959 (2018) - [i7]Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos, Daniel Zoran:
Learned Deformation Stability in Convolutional Neural Networks. CoRR abs/1804.04438 (2018) - [i6]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 abs/1807.01281 (2018) - [i5]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. CoRR abs/1809.11044 (2018) - 2017
- [c2]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: 3191-3199 - [i4]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:
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR abs/1711.08378 (2017) - 2016
- [i3]Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, Raia Hadsell:
Progressive Neural Networks. CoRR abs/1606.04671 (2016) - [i2]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 abs/1612.00796 (2016) - [i1]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 abs/1612.08810 (2016) - 2015
- [c1]Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli:
The local low-dimensionality of natural images. ICLR 2015
Coauthor Index
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