Weber, Théophane

26 publications

TMLR 2023 Equivariant MuZero Andreea Deac, Theophane Weber, George Papamakarios

ICML 2023 Investigating the Role of Model-Based Learning in Exploration and Transfer Jacob C Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B Hamrick

ICLR 2023 Learning to Induce Causal Structure Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende

ICML 2023 Quantile Credit Assignment Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Remi Munos

NeurIPS 2022 Large-Scale Retrieval for Reinforcement Learning Peter Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy Lillicrap

ICMLW 2022 Learning to Induce Causal Structure Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Matthew Botvinick, Theophane Weber, Michael Curtis Mozer, Danilo Jimenez Rezende

ICLR 2022 Procedural Generalization by Planning with Self-Supervised World Models Ankesh Anand, Jacob C Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B Hamrick

ICML 2022 Retrieval-Augmented Reinforcement Learning Anirudh Goyal, Abram Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter C Humphreys, Ksenia Konyushova, Michal Valko, Simon Osindero, Timothy Lillicrap, Nicolas Heess, Charles Blundell

ICML 2021 Counterfactual Credit Assignment in Model-Free Reinforcement Learning Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos

ICML 2021 Muesli: Combining Improvements in Policy Optimization Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado Van Hasselt

ICLR 2021 On the Role of Planning in Model-Based Deep Reinforcement Learning Jessica B Hamrick, Abram L. Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Veličković, Theophane Weber

NeurIPSW 2020 A Case for New Neural Networks Smoothness Constraints Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed

AISTATS 2020 Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions Lars Buesing, Nicolas Heess, Theophane Weber

ICLR 2020 Combining Q-Learning and Search with Amortized Value Estimates Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia

NeurIPS 2020 Value-Driven Hindsight Modelling Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

ICML 2019 An Investigation of Model-Free Planning Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sebastien Racaniere, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy Lillicrap

AISTATS 2019 Credit Assignment Techniques in Stochastic Computation Graphs Théophane Weber, Nicolas Heess, Lars Buesing, David Silver

ICLR 2019 Temporal Difference Variational Auto-Encoder Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

ICLR 2019 Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sebastien Racaniere, Arthur Guez, Jean-Baptiste Lespiau

ICML 2018 Learning to Search with MCTSnets Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Remi Munos, David Silver

NeurIPS 2018 Relational Recurrent Neural Networks Adam Santoro, Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap

NeurIPS 2018 Single-Agent Policy Tree Search with Guarantees Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber

NeurIPS 2017 Imagination-Augmented Agents for Deep Reinforcement Learning Sébastien Racanière, Theophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra

NeurIPS 2017 Visual Interaction Networks: Learning a Physics Simulator from Video Nicholas Watters, Daniel Zoran, Theophane Weber, Peter Battaglia, Razvan Pascanu, Andrea Tacchetti

NeurIPS 2016 Attend, Infer, Repeat: Fast Scene Understanding with Generative Models S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton

NeurIPS 2015 Gradient Estimation Using Stochastic Computation Graphs John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel