Information decomposition in complex systems via machine learning

arXiv:2307.04755v2 Announce Type: replace
Abstract: One of the fundamental steps toward understanding a complex system is identifying variation at the scale of the system's components that is most relevant to behavior on a macroscopic scale. Mutual information provides a natural means of linking variation across scales of a system due to its independence of functional relationship between observables. However, characterizing the manner in which information is distributed across a set of observables is computationally challenging and generally infeasible beyond a …

abstract arxiv behavior complex systems components cond-mat.soft cs.it cs.lg information machine machine learning math.it natural physics.data-an scale systems type understanding variation via