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arXiv · 1903.00201

Non-linear ICA based on Cramer-Wold metric

Przemysław Spurek·Aleksandra Nowak·Jacek Tabor·Łukasz Maziarka·Stanisław Jastrzębski
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Abstract

Non-linear source separation is a challenging open problem with many applications. We extend a recently proposed Adversarial Non-linear ICA (ANICA) model, and introduce Cramer-Wold ICA (CW-ICA). In contrast to ANICA we use a simple, closed--form optimization target instead of a discriminator--based independence measure. Our results show that CW-ICA achieves comparable results to ANICA, while foregoing the need for adversarial training.

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Przemysław Spurek, Aleksandra Nowak, Jacek Tabor, Łukasz Maziarka, Stanisław Jastrzębski. 2019-03-01. Non-linear ICA based on Cramer-Wold metric. https://doi.org/10.1007/978-3-030-63836-8_25

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