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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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COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration


May 22, 2019
Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P. Burgess, Alexander Lerchner


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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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Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs


Jan 21, 2019
Nicholas Watters, Loic Matthey, Christopher P. Burgess, 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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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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