A Bayesian Variational principle for dynamic Self Organizing Maps

Published 24 Aug 2022 in cs.LG, cs.NE, and stat.ML | (2208.11337v1)

Abstract: We propose organisation conditions that yield a method for training SOM with adaptative neighborhood radius in a variational Bayesian framework. This method is validated on a non-stationary setting and compared in an high-dimensional setting with an other adaptative method.

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