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Towards a Definition of Disentangled Representations

Dec 05, 2018
Irina Higgins, David Amos, David Pfau, Sebastien Racaniere, Loic Matthey, Danilo Rezende, Alexander Lerchner


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Unsupervised Predictive Memory in a Goal-Directed Agent

Mar 28, 2018
Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matt Botvinick, Demis Hassabis, Timothy Lillicrap


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Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions

Feb 28, 2018
Scott Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Rezende, Oriol Vinyals, Nando de Freitas


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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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Interaction Networks for Learning about Objects, Relations and Physics

Dec 01, 2016
Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Rezende, Koray Kavukcuoglu

* Published in NIPS 2016 

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Normalizing Flows on Riemannian Manifolds

Nov 09, 2016
Mevlana C. Gemici, Danilo Rezende, Shakir Mohamed

* 3 pages, 2 figures, Submitted to Workshop on Bayesian Deep Learning at NIPS 2016 

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Towards Principled Unsupervised Learning

Dec 03, 2015
Ilya Sutskever, Rafal Jozefowicz, Karol Gregor, Danilo Rezende, Tim Lillicrap, Oriol Vinyals


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