Measure of Similarity between GMMs Based on Autoencoder-Generated Gaussian Component Representations

A novel similarity measure between Gaussian mixture models (GMMs), based on similarities between the low-dimensional representations of individual GMM components and obtained using deep autoencoder architectures, is proposed in this paper. Two different approaches built upon these architectures are...

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Hlavní autoři:	Vladimir Kalušev, Branislav Popović, Marko Janev, Branko Brkljač, Nebojša Ralević
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2023-05-01
Edice:	Axioms
Témata:	Gaussian mixture models autoencoders KL divergence classification machine learning
On-line přístup:	https://www.mdpi.com/2075-1680/12/6/535
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