Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Theophane Weber

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


  Access Paper or Ask Questions

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


  Access Paper or Ask Questions

A case for new neural network smoothness constraints


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


  Access Paper or Ask Questions

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


  Access Paper or Ask Questions

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


  Access Paper or Ask Questions

Causally Correct Partial Models for Reinforcement Learning


Feb 07, 2020
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


  Access Paper or Ask Questions

Combining Q-Learning and Search with Amortized Value Estimates


Jan 10, 2020
Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia

* Published as a conference paper at ICLR 2020 

  Access Paper or Ask Questions

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


Oct 15, 2019
Lars Buesing, Nicolas Heess, Theophane Weber


  Access Paper or Ask Questions

Unsupervised Doodling and Painting with Improved SPIRAL


Oct 02, 2019
John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami

* See https://learning-to-paint.github.io for an interactive version of this paper, with videos 

  Access Paper or Ask Questions

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search


Nov 15, 2018
Lars Buesing, Theophane Weber, Yori Zwols, Sebastien Racaniere, Arthur Guez, Jean-Baptiste Lespiau, Nicolas Heess


  Access Paper or Ask Questions

Relational recurrent neural networks


Jun 28, 2018
Adam Santoro, Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap


  Access Paper or Ask Questions

Learning and Querying Fast Generative Models for Reinforcement Learning


Feb 08, 2018
Lars Buesing, Theophane Weber, Sebastien Racaniere, S. M. Ali Eslami, Danilo Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra


  Access Paper or Ask Questions

Visual Interaction Networks


Jun 05, 2017
Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter Battaglia, Daniel Zoran


  Access Paper or Ask Questions

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


Aug 12, 2016
S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton


  Access Paper or Ask Questions

Deep Reinforcement Learning in Large Discrete Action Spaces


Apr 04, 2016
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin


  Access Paper or Ask Questions

Gradient Estimation Using Stochastic Computation Graphs


Jan 05, 2016
John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

* Advances in Neural Information Processing Systems 28 (NIPS 2015) 

  Access Paper or Ask Questions

Automated Variational Inference in Probabilistic Programming


Jan 07, 2013
David Wingate, Theophane Weber


  Access Paper or Ask Questions