Autoencoding topology

Eric O. Korman

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arXiv · 1803.00156

Autoencoding topology

Eric O. Korman

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Abstract

The problem of learning a manifold structure on a dataset is framed in terms of a generative model, to which we use ideas behind autoencoders (namely adversarial/Wasserstein autoencoders) to fit deep neural networks. From a machine learning perspective, the resulting structure, an atlas of a manifold, may be viewed as a combination of dimensionality reduction and "fuzzy" clustering.

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Eric O. Korman. 2018-03-01. Autoencoding topology. https://arxiv.org/abs/1803.00156

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