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Bibliographic Details
Main Authors:	Argouarc'h, Elouan, Desbouvries, François, Barat, Eric, Kawasaki, Eiji, Dautremer, Thomas
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2501.02989
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This paper proposes an extension of standard mixture stochastic models, by replacing the constant mixture weights with functional weights defined using a classifier. Classifier Weighted Mixtures enable straightforward density evaluation, explicit sampling, and enhanced expressivity in variational estimation problems, without increasing the number of components nor the complexity of the mixture components.