Movie table: tangible interaction with movies. - David Raposo; Teresa Chambel (MindTrek, 2009)

A model of structure learning, inference, and generation for scene understanding. - David Raposo; Peter Dayan; Demis Hassabis; Peter W. Battaglia (CogSci, 2017)

Discovering objects and their relations from entangled scene representations. - David Raposo; Adam Santoro; David G. T. Barrett; Razvan Pascanu; Tim Lillicrap; Peter W. Battaglia (ICLR (Workshop), 2017)

A simple neural network module for relational reasoning. - Adam Santoro; David Raposo; David G. T. Barrett; Mateusz Malinowski; Razvan Pascanu; Peter W. Battaglia; Tim Lillicrap (NIPS, 2017)

Relational recurrent neural networks. - Adam Santoro; Ryan Faulkner 001; David Raposo; Jack W. Rae; Mike Chrzanowski; Theophane Weber; Daan Wierstra; Oriol Vinyals; Razvan Pascanu; Timothy P. Lillicrap (NeurIPS, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Deep Reinforcement Learning. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (CoRR, 2018)

Hyperbolic Attention Networks. - Çaglar Gülçehre; Misha Denil; Mateusz Malinowski; Ali Razavi; Razvan Pascanu; Karl Moritz Hermann; Peter W. Battaglia; Victor Bapst; David Raposo; Adam Santoro; Nando de Freitas (ICLR (Poster), 2019)

Deep reinforcement learning with relational inductive biases. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (ICLR (Poster), 2019)

An Investigation of Model-Free Planning. - Arthur Guez; Mehdi Mirza; Karol Gregor; Rishabh Kabra; Sébastien Racanière; Theophane Weber; David Raposo; Adam Santoro; Laurent Orseau; Tom Eccles; Greg Wayne; David Silver; et al. (ICML, 2019)

Causal Reasoning from Meta-reinforcement Learning. - Ishita Dasgupta 001; Jane X. Wang; Silvia Chiappa; Jovana Mitrovic; Pedro A. Ortega; David Raposo; Edward Hughes 001; Peter W. Battaglia; Matthew M. Botvinick; Zeb Kurth-Nelson (CoRR, 2019)

Is coding a relevant metaphor for building AI? A commentary on "Is coding a relevant metaphor for the brain?", by Romain Brette. - Adam Santoro; Felix Hill; David G. T. Barrett; David Raposo; Matthew M. Botvinick; Timothy P. Lillicrap (CoRR, 2019)

Rapid Task-Solving in Novel Environments. - Samuel Ritter; Ryan Faulkner 001; Laurent Sartran; Adam Santoro; Matthew M. Botvinick; David Raposo (ICLR, 2021)

Symbolic Behaviour in Artificial Intelligence. - Adam Santoro; Andrew K. Lampinen; Kory W. Mathewson; Timothy P. Lillicrap; David Raposo (CoRR, 2021)

Synthetic Returns for Long-Term Credit Assignment. - David Raposo; Samuel Ritter; Adam Santoro; Greg Wayne; Theophane Weber; Matt M. Botvinick; Hado van Hasselt; H. Francis Song (CoRR, 2021)

A data-driven approach for learning to control computers. - Peter Conway Humphreys; David Raposo; Tobias Pohlen; Gregory Thornton; Rachita Chhaparia; Alistair Muldal; Josh Abramson; Petko Georgiev; Adam Santoro; Timothy P. Lillicrap (ICML, 2022)

A data-driven approach for learning to control computers. - Peter Conway Humphreys; David Raposo; Toby Pohlen; Gregory Thornton; Rachita Chhaparia; Alistair Muldal; Josh Abramson; Petko Georgiev; Alex Goldin; Adam Santoro; Timothy P. Lillicrap (CoRR, 2022)

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models. - David Raposo; Samuel Ritter; Blake A. Richards; Timothy P. Lillicrap; Peter Conway Humphreys; Adam Santoro (CoRR, 2024)