The local low-dimensionality of natural images. - Olivier J. Hénaff; Johannes Ballé; Neil C. Rabinowitz; Eero P. Simoncelli (ICLR, 2015)

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; et al. (CoRR, 2016)

Progressive Neural Networks. - Andrei A. Rusu; Neil C. Rabinowitz; Guillaume Desjardins; Hubert Soyer; James Kirkpatrick; Koray Kavukcuoglu; Razvan Pascanu; Raia Hadsell (CoRR, 2016)

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 001; Thomas Degris (ICML, 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; et al. (CoRR, 2017)

On the importance of single directions for generalization. - Ari S. Morcos; David G. T. Barrett; Neil C. Rabinowitz; Matthew M. Botvinick (ICLR (Poster), 2018)

Machine Theory of Mind. - Neil C. Rabinowitz; Frank Perbet; H. Francis Song; Chiyuan Zhang; S. M. Ali Eslami; Matthew M. Botvinick (ICML, 2018)

Learned Deformation Stability in Convolutional Neural Networks. - Avraham Ruderman; Neil C. Rabinowitz; Ari S. Morcos; Daniel Zoran (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; et al. (CoRR, 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)

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; et al. (Nat., 2018)

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 (ICLR (Poster), 2019)

Meta-learners' learning dynamics are unlike learners'. - Neil C. Rabinowitz (CoRR, 2019)

Meta-learning of Sequential Strategies. - Pedro A. Ortega; Jane X. Wang; Mark Rowland 001; Tim Genewein; Zeb Kurth-Nelson; Razvan Pascanu; Nicolas Heess; Joel Veness; Alexander Pritzel; Pablo Sprechmann; Siddhant M. Jayakumar; Tom McGrath; et al. (CoRR, 2019)

Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions. - János Kramár; Neil C. Rabinowitz; Tom Eccles; Andrea Tacchetti (COIN(E)@AAMAS, 2020)

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. - Çaglar Gülçehre; Tom Le Paine; Bobak Shahriari; Misha Denil; Matt Hoffman 001; Hubert Soyer; Richard Tanburn; Steven Kapturowski; Neil C. Rabinowitz; Duncan Williams; Gabriel Barth-Maron; Ziyu Wang 001; et al. (ICLR, 2020)

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. - Jane Wang 001; 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; et al. (NeurIPS Datasets and Benchmarks, 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; et al. (CoRR, 2021)

Tell me why! Explanations support learning relational and causal structure. - Andrew K. Lampinen; Nicholas A. Roy; Ishita Dasgupta 001; Stephanie C. Y. Chan; Allison C. Tam; James L. McClelland; Chen Yan; Adam Santoro; Neil C. Rabinowitz; Jane X. Wang; Felix Hill (ICML, 2022)

Explainability Via Causal Self-Talk. - Nicholas A. Roy; Junkyung Kim; Neil C. Rabinowitz (NeurIPS, 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 001; Andrea Banino; Felix Hill (NeurIPS, 2022)