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Representation Matters: Improving Perception and Exploration for Robotics

Nov 03, 2020
Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin Riedmiller


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Representation learning for improved interpretability and classification accuracy of clinical factors from EEG

Oct 30, 2020
Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic, Katie Link, Pramod Gupta, Julia Klawohn, Greg Hajcak


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Disentangling by Subspace Diffusion

Jun 23, 2020
David Pfau, Irina Higgins, Aleksandar Botev, Sébastien Racanière

* 21 pages, 13 figures 

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Disentangled Cumulants Help Successor Representations Transfer to New Tasks

Nov 25, 2019
Christopher Grimm, Irina Higgins, Andre Barreto, Denis Teplyashin, Markus Wulfmeier, Tim Hertweck, Raia Hadsell, Satinder Singh


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Hamiltonian Generative Networks

Sep 30, 2019
Peter Toth, Danilo Jimenez Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins


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Equivariant Hamiltonian Flows

Sep 30, 2019
Danilo Jimenez Rezende, Sébastien Racanière, Irina Higgins, Peter Toth


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A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning

May 29, 2019
Sunny Duan, Nicholas Watters, Loic Matthey, Christopher P. Burgess, Alexander Lerchner, Irina Higgins


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MONet: Unsupervised Scene Decomposition and Representation

Jan 22, 2019
Christopher P. Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, Alexander Lerchner


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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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Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies

Aug 20, 2018
Alessandro Achille, Tom Eccles, Loic Matthey, Christopher P. Burgess, Nick Watters, Alexander Lerchner, Irina Higgins


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SCAN: Learning Hierarchical Compositional Visual Concepts

Jun 06, 2018
Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P Burgess, Matko Bosnjak, Murray Shanahan, Matthew Botvinick, Demis Hassabis, Alexander Lerchner


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DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Jun 06, 2018
Irina Higgins, Arka Pal, Andrei A. Rusu, Loic Matthey, Christopher P Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner

* ICML 2017 

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Understanding disentangling in $β$-VAE

Apr 10, 2018
Christopher P. Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner

* Presented at the 2017 NIPS Workshop on Learning Disentangled Representations 

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Early Visual Concept Learning with Unsupervised Deep Learning

Sep 20, 2016
Irina Higgins, Loic Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner


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