Learning minimal representations of stochastic processes with variational autoencoders

Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. Due to their intrinsic randomness and uncertainty, they are, however, difficult to characterize. Here, we introduce an unsupervised machine learning approach to determi...

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Vydané v:	Physical review. E Ročník 110; číslo 1; s. L012102
Hlavní autori:	Fernández-Fernández, Gabriel, Manzo, Carlo, Lewenstein, Maciej, Dauphin, Alexandre, Muñoz-Gil, Gorka
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.07.2024
ISSN:	2470-0053, 2470-0053
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