David Raposo

According to our database, David Raposo authored at least 18 papers between 2009 and 2024.

Collaborative distances:

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

2024

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

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

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

Proceedings of the International Conference on Machine Learning, 2022

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

Symbolic Behaviour in Artificial Intelligence.

Adam Santoro, Andrew K. Lampinen, Kory W. Mathewson, Timothy P. Lillicrap, David Raposo

CoRR, 2021

Rapid Task-Solving in Novel Environments.

Samuel Ritter, Ryan Faulkner, Laurent Sartran, Adam Santoro, Matthew M. Botvinick, David Raposo

Proceedings of the 9th International Conference on Learning Representations, 2021

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

Causal Reasoning from Meta-reinforcement Learning.

Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson

CoRR, 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, Timothy P. Lillicrap

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep reinforcement learning with relational inductive biases.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

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

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

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

2018

Relational Deep Reinforcement Learning.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

CoRR, 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, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu

CoRR, 2018

Relational recurrent neural networks.

Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy P. Lillicrap

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 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

Proceedings of the 5th International Conference on Learning Representations, 2017

A model of structure learning, inference, and generation for scene understanding.

David Raposo, Peter Dayan, Demis Hassabis, Peter W. Battaglia

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2009

Movie table: tangible interaction with movies.

David Raposo, Teresa Chambel

Proceedings of the 13th International Academic MindTrek Conference: Everyday Life in the Ubiquitous Era, 2009