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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


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Shaping Belief States with Generative Environment Models for RL

Jun 24, 2019
Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aaron van den Oord

* pre-print 

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TF-Replicator: Distributed Machine Learning for Researchers

Feb 01, 2019
Peter Buchlovsky, David Budden, Dominik Grewe, Chris Jones, John Aslanides, Frederic Besse, Andy Brock, Aidan Clark, Sergio Gómez Colmenarejo, Aedan Pope, Fabio Viola, Dan Belov


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Encoding Spatial Relations from Natural Language

Jul 05, 2018
Tiago Ramalho, Tomáš Kočiský, Frederic Besse, S. M. Ali Eslami, Gábor Melis, Fabio Viola, Phil Blunsom, Karl Moritz Hermann


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Learning models for visual 3D localization with implicit mapping

Jul 04, 2018
Dan Rosenbaum, Frederic Besse, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami


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Temporal Difference Variational Auto-Encoder

Jun 11, 2018
Karol Gregor, Frederic Besse

* 13 pages, 7 figures 

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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


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Convolution by Evolution: Differentiable Pattern Producing Networks

Jun 08, 2016
Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra


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Towards Conceptual Compression

Apr 29, 2016
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra

* 14 pages, 13 figures 

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