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Theophane Weber

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DiscoGen: Learning to Discover Gene Regulatory Networks

Apr 12, 2023
Nan Rosemary Ke, Sara-Jane Dunn, Jorg Bornschein, Silvia Chiappa, Melanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane Wang, Theophane Weber, David Barrett, Matthew Botvinick, Anirudh Goyal, Mike Mozer, Danilo Rezende

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Learning to Induce Causal Structure

Apr 11, 2022
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jorg Bornschein, Theophane Weber, Anirudh Goyal, Matthew Botvinic, Michael Mozer, Danilo Jimenez Rezende

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Retrieval-Augmented Reinforcement Learning

Mar 09, 2022
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adria Puigdomenech Badia, Arthur Guez, Mehdi Mirza, Peter C. Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy Lillicrap, Nicolas Heess, Charles Blundell

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Muesli: Combining Improvements in Policy Optimization

Apr 13, 2021
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt

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Synthetic Returns for Long-Term Credit Assignment

Feb 24, 2021
David Raposo, Sam Ritter, Adam Santoro, Greg Wayne, Theophane Weber, Matt Botvinick, Hado van Hasselt, Francis Song

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A case for new neural network smoothness constraints

Dec 21, 2020
Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed

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Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban

Oct 03, 2020
Peter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber

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Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning

Apr 23, 2020
Giambattista Parascandolo, Lars Buesing, Josh Merel, Leonard Hasenclever, John Aslanides, Jessica B. Hamrick, Nicolas Heess, Alexander Neitz, Theophane Weber

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