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Found 3 papers, 1 papers with code
TMI: Thermodynamic inference of data manifolds
The Gibbs-Boltzmann distribution offers a physically interpretable way to massively reduce the dimensionality of high dimensional probability distributions where the extensive variables are `features' and the intensive variables are `descriptors'.
Introducing user-prescribed constraints in Markov chains for nonlinear dimensionality reduction
The central component of many of these methods is a symmetric kernel that quantifies the vicinity between pairs of data points and a kernel-induced Markov chain on the data.
Entropy production rate as a criterion for inconsistency in decision theory
Pairwise comparison matrices (PCMs) are regularly used to solve multiple-criteria decision-making (MCDM) problems, for example, using Saaty's analytic hierarchy process (AHP) framework.
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