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arXiv · 2001.04147

WICA: nonlinear weighted ICA

Andrzej Bedychaj·Przemysław Spurek·Aleksandra Nowak·Jacek Tabor
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Abstract

Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. In this paper we construct a new nonlinear ICA model, called WICA, which obtains better and more stable results than other algorithms. A crucial tool is given by a new efficient method of verifying nonlinear dependence with the use of computation of correlation coefficients for normally weighted data. In addition, authors propose a new baseline nonlinear mixing to perform comparable experiments, and a~reliable measure which allows fair comparison of nonlinear models. Our code for WICA is available on Github https://github.com/gmum/wica.

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Andrzej Bedychaj, Przemysław Spurek, Aleksandra Nowak, Jacek Tabor. 2020-01-13. WICA: nonlinear weighted ICA. https://arxiv.org/abs/2001.04147

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