Estimating the Unique Information of Continuous Variables.

ABSTRACT: The integration and transfer of information from multiple sources to multiple targets is a core motive of neural systems. The emerging field of partial information decomposition (PID) provides a novel information-theoretic lens into these mechanisms by identifying synergistic, redundant, and unique contributions to the mutual information between one and several variables. While many works have studied aspects of PID for Gaussian and discrete distributions, the case of general continuous distributions is still uncharted territory. In this work we present a method for estimating the unique information in continuous distributions, for the case of one versus two variables. Our method solves the associated optimization problem over the space of distributions with fixed bivariate marginals by co

SUBMITTER: Pakman A 

PROVIDER: S-EPMC9137417 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature