Theophane Weber

60 papers A* 16A 2Journal 32Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Advancing Geometry with AI: Multi-agent Generation of Polytopes. CoRR Grzegorz Swirszcz, Adam Zsolt Wagner, Geordie Williamson, Sam Blackwell, Bogdan Georgiev, Alex Davies, S. M. Ali Eslami, Sébastien Racanière, Theophane Weber, Pushmeet Kohli
2025	J	`jnl`	Drums of high width. CoRR Alex Davies, Prateek Gupta, Sébastien Racanière, Grzegorz Swirszcz, Adam Zsolt Wagner, Theophane Weber, Geordie Williamson
2023	J	`jnl`	DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
2023	J	`jnl`	Equivariant MuZero. Trans. Mach. Learn. Res. Andreea Deac, Theophane Weber, George Papamakarios
2023	A*	`conf`	Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
2023	A*	`conf`	Quantile Credit Assignment. ICML Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos
2022	A*	`conf`	Large-Scale Retrieval for Reinforcement Learning. NeurIPS Peter Conway Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy P. Lillicrap
2022	J	`jnl`	Learning to Induce Causal Structure. CoRR Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
2022	A*	`conf`	Procedural generalization by planning with self-supervised world models. ICLR Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B. Hamrick
2022	A*	`conf`	Retrieval-Augmented Reinforcement Learning. ICML Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter Conway Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
2022	J	`jnl`	Retrieval-Augmented Reinforcement Learning. CoRR Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
2021	A*	`conf`	Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 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, Rémi Munos
2021	A*	`conf`	Muesli: Combining Improvements in Policy Optimization. ICML Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
2021	J	`jnl`	Muesli: Combining Improvements in Policy Optimization. CoRR Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
2021	A*	`conf`	On the role of planning in model-based deep reinforcement learning. ICLR Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber
2021	J	`jnl`	Synthetic Returns for Long-Term Credit Assignment. CoRR David Raposo, Samuel Ritter, Adam Santoro, Greg Wayne, Theophane Weber, Matt M. Botvinick, Hado van Hasselt, H. Francis Song
2020	—	`conf`	A case for new neural network smoothness constraints. ICBINB@NeurIPS Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
2020	J	`jnl`	A case for new neural network smoothness constraints. CoRR Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
2020	A	`conf`	Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions. AISTATS Lars Buesing, Nicolas Heess, Theophane Weber
2020	J	`jnl`	Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban. CoRR Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber
2020	J	`jnl`	Causally Correct Partial Models for Reinforcement Learning. CoRR Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing
2020	A*	`conf`	Combining Q-Learning and Search with Amortized Value Estimates. ICLR Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia
2020	J	`jnl`	Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. CoRR Giambattista Parascandolo, Lars Buesing, Josh Merel, Leonard Hasenclever, John Aslanides, Jessica B. Hamrick, Nicolas Heess, Alexander Neitz, Theophane Weber
2020	A*	`conf`	Value-driven Hindsight Modelling. NeurIPS Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess
2019	A*	`conf`	An Investigation of Model-Free Planning. ICML 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
2019	J	`jnl`	Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions. CoRR Lars Buesing, Nicolas Heess, Theophane Weber
2019	J	`jnl`	Combining Q-Learning and Search with Amortized Value Estimates. CoRR Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia
2019	—	`conf`	Temporal Difference Variational Auto-Encoder. ICLR Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber
2019	J	`jnl`	Unsupervised Doodling and Painting with Improved SPIRAL. CoRR John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami
2019	—	`conf`	Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search. ICLR (Poster) Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau
2018	J	`jnl`	Learning and Querying Fast Generative Models for Reinforcement Learning. CoRR Lars Buesing, Theophane Weber, Sébastien Racanière, S. M. Ali Eslami, Danilo Jimenez Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra
2018	A*	`conf`	Learning to Search with MCTSnets. ICML Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
2018	A*	`conf`	Relational recurrent neural networks. NeurIPS Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy P. Lillicrap
2018	J	`jnl`	Relational recurrent neural networks. CoRR Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy P. Lillicrap
2018	A*	`conf`	Single-Agent Policy Tree Search With Guarantees. NeurIPS Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber
2018	J	`jnl`	Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search. CoRR Lars Buesing, Theophane Weber, Yori Zwols, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau, Nicolas Heess
2017	J	`jnl`	Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR 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, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
2017	—	`conf`	Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS Sébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, Demis Hassabis, David Silver, Daan Wierstra
2017	J	`jnl`	Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra
2017	J	`jnl`	Learning model-based planning from scratch. CoRR Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sébastien Racanière, David P. Reichert, Theophane Weber, Daan Wierstra, Peter W. Battaglia
2017	J	`jnl`	Visual Interaction Networks. CoRR Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran
2017	—	`conf`	Visual Interaction Networks: Learning a Physics Simulator from Video. NIPS Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti
2016	J	`jnl`	An Optimization Platform for Digital Predistortion of Power Amplifiers. IEEE Des. Test Hari Chauhan, Marvin Onabajo, Vladimir Kvartenko, Robin Coxe, Theophane Weber
2016	—	`conf`	Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. NIPS S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton
2016	J	`jnl`	Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. CoRR S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton
2015	—	`conf`	Gradient Estimation Using Stochastic Computation Graphs. NIPS John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel
2015	J	`jnl`	Gradient Estimation Using Stochastic Computation Graphs. CoRR John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel
2014	J	`jnl`	Correlation Decay in Random Decision Networks. Math. Oper. Res. David Gamarnik, David A. Goldberg, Theophane Weber
2013	J	`jnl`	Automated Variational Inference in Probabilistic Programming CoRR David Wingate, Theophane Weber
2012	J	`jnl`	Accelerating Inference: towards a full Language, Compiler and Hardware stack CoRR Shawn Hershey, Jeffrey Bernstein, Bill Bradley, Andrew Schweitzer, Noah Stein, Theophane Weber, Benjamin Vigoda
2012	J	`jnl`	Quantifying Statistical Interdependence, Part III: Neural Comput. Justin Dauwels, Theophane Weber, François B. Vialatte, Toshimitsu Musha, Andrzej Cichocki
2010	A	`conf`	Low power logic for statistical inference. ISLPED Benjamin Vigoda, David Reynolds, Jeffrey Bernstein, Theophane Weber, Bill Bradley
2010	A*	`conf`	PTAS for Maximum Weight Independent Set Problem with Random Weights in Bounded Degree Graphs. SODA David Gamarnik, David A. Goldberg, Theophane Weber
2009	J	`jnl`	Correlation Decay in Random Decision Networks CoRR David Gamarnik, David A. Goldberg, Theophane Weber
2009	J	`jnl`	Quantifying Statistical Interdependence by Message Passing on Graphs - Part I: One-Dimensional Point Processes. Neural Comput. Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki
2009	J	`jnl`	Quantifying Statistical Interdependence by Message Passing on Graphs - Part II: Multidimensional Point Processes. Neural Comput. Justin Dauwels, François B. Vialatte, Theophane Weber, Toshimitsu Musha, Andrzej Cichocki
2008	—	`conf`	An Exemplar-Based Statistical Model for the Dynamics of Neural Synchrony. ICONIP (1) Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki
2008	—	`conf`	Analyzing brain signals by combinatorial optimization. Allerton Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki
2008	—	`conf`	On Similarity Measures for Spike Trains. ICONIP (1) Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki