WICA: nonlinear weighted ICA

• URL: http://arxiv.org/abs/2001.04147v2
• Date: Wed, 9 Dec 2020 21:37:54 GMT
• Title: WICA: nonlinear weighted ICA
• Authors: Andrzej Bedychaj, Przemys{\l}aw Spurek, Aleksandra Nowak, Jacek Tabor
• Abstract summary: Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. We construct a new nonlinear ICA model, called WICA, which obtains better and more stable results than other algorithms.
• Score: 72.02008296553318
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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