Theophane Weber

According to our database, Theophane Weber authored at least 57 papers between 2008 and 2023.

Collaborative distances:

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

2023

DiscoGen: Learning to Discover Gene Regulatory Networks.

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

CoRR, 2023

Equivariant MuZero.

Andreea Deac, Théophane Weber, George Papamakarios

CoRR, 2023

Laser: Latent Set Representations for 3D Generative Modeling.

Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosália G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende

CoRR, 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

Proceedings of the International Conference on Machine Learning, 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, Rémi Munos

Proceedings of the International Conference on Machine Learning, 2023

Learning to Induce Causal Structure.

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning to Induce Causal Structure.

Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

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

CoRR, 2022

Large-Scale Retrieval for Reinforcement Learning.

Peter C. Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy P. Lillicrap

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Retrieval-Augmented Reinforcement Learning.

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

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the Tenth International Conference on Learning Representations, 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

Neural Recursive Belief States in Multi-Agent Reinforcement Learning.

Pol Moreno, Edward Hughes, Kevin R. McKee, Bernardo Ávila Pires, Théophane Weber

CoRR, 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, Rémi Munos

Proceedings of the 38th International Conference on Machine Learning, 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

Proceedings of the 38th International Conference on Machine Learning, 2021

On the role of planning in model-based deep reinforcement learning.

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

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

2020

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

Thomas Mesnard, Théophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Arthur Guez, Marcus Hutter, Lars Buesing, Rémi Munos

CoRR, 2020

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

Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber

CoRR, 2020

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.

Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Péter Karkus, Sébastien Racanière, Lars Buesing, Timothy P. Lillicrap, Nicolas Heess

CoRR, 2020

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

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

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

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

CoRR, 2020

Value-driven Hindsight Modelling.

Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the 8th International Conference on Learning Representations, 2020

A case for new neural network smoothness constraints.

Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions.

Lars Buesing, Nicolas Heess, Theophane Weber

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Unsupervised Doodling and Painting with Improved SPIRAL.

John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami

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

Temporal Difference Variational Auto-Encoder.

Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

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

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.

Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau

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

Credit Assignment Techniques in Stochastic Computation Graphs.

Théophane Weber, Nicolas Heess, Lars Buesing, David Silver

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning and Querying Fast Generative Models for Reinforcement Learning.

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

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

Single-Agent Policy Tree Search With Guarantees.

Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber

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

Learning to Search with MCTSnets.

Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.

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

CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

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

CoRR, 2017

Visual Interaction Networks.

Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran

CoRR, 2017

Learning model-based planning from scratch.

Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sébastien Racanière, David P. Reichert, Theophane Weber, Daan Wierstra, Peter W. Battaglia

CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.

Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti

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

Imagination-Augmented Agents for Deep Reinforcement Learning.

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

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

2016

An Optimization Platform for Digital Predistortion of Power Amplifiers.

Hari Chauhan, Marvin Onabajo, Vladimir Kvartenko, Robin Coxe, Theophane Weber

IEEE Des. Test, 2016

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.

S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Gradient Estimation Using Stochastic Computation Graphs.

John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Correlation Decay in Random Decision Networks.

David Gamarnik, David A. Goldberg, Theophane Weber

Math. Oper. Res., 2014

2013

Automated Variational Inference in Probabilistic Programming

David Wingate, Theophane Weber

CoRR, 2013

2012

Quantifying Statistical Interdependence, Part III: <i>N</i> > 2 Point Processes.

Justin Dauwels, Theophane Weber, François B. Vialatte, Toshimitsu Musha, Andrzej Cichocki

Neural Comput., 2012

Accelerating Inference: towards a full Language, Compiler and Hardware stack

Shawn Hershey, Jeffrey Bernstein, Bill Bradley, Andrew Schweitzer, Noah Stein, Theophane Weber, Benjamin Vigoda

CoRR, 2012

2010

To Wave or Not to Wave? Order Release Policies for Warehouses with an Automated Sorter.

Jérémie Gallien, Théophane Weber

Manuf. Serv. Oper. Manag., 2010

PTAS for Maximum Weight Independent Set Problem with Random Weights in Bounded Degree Graphs.

David Gamarnik, David A. Goldberg, Theophane Weber

Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Low power logic for statistical inference.

Benjamin Vigoda, David Reynolds, Jeffrey Bernstein, Theophane Weber, Bill Bradley

Proceedings of the 2010 International Symposium on Low Power Electronics and Design, 2010

2009

Quantifying Statistical Interdependence by Message Passing on Graphs - Part II: Multidimensional Point Processes.

Justin Dauwels, François B. Vialatte, Theophane Weber, Toshimitsu Musha, Andrzej Cichocki

Neural Comput., 2009

Quantifying Statistical Interdependence by Message Passing on Graphs - Part I: One-Dimensional Point Processes.

Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki

Neural Comput., 2009

2008

An Exemplar-Based Statistical Model for the Dynamics of Neural Synchrony.

Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

On Similarity Measures for Spike Trains.

Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Choosing the cost vector of the linear programming approach to approximate dynamic programming.

Daniela Pucci de Farias, Théophane Weber

Proceedings of the 47th IEEE Conference on Decision and Control, 2008

Analyzing brain signals by combinatorial optimization.

Justin Dauwels, François B. Vialatte, Theophane Weber, Andrzej Cichocki

Proceedings of the 46th Annual Allerton Conference on Communication, 2008