Mean mutual information and symmetry breaking for finite random fields

DOI10.1214/11-AIHP416zbMath1259.94032MaRDI QIDQ424692

Jérôme Buzzi, Lorenzo Zambotti

Publication date: 4 June 2012

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aihp/1334148202

zbMATH Keywords

entropymutual informationexchangeable random variablesdiscrete probabilityneural complexity

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Combinatorial probability (60C05) Measures of information, entropy (94A17)

Related Items (3)

Dynamical intricacy and average sample complexity for random bundle transformations ⋮ Dynamical intricacy and average sample complexity of amenable group actions ⋮ Approximate maximizers of intricacy functionals

Cites Work

• Approximate maximizers of intricacy functionals
• Analytical description of the evolution of neural networks: Learning rules and complexity
• Nonnegative entropy measures of multivariate symmetric correlations
• Polymatroidal dependence structure of a set of random variables
• Information Inequalities for Joint Distributions, With Interpretations and Applications
• Random Fragmentation and Coagulation Processes
• Elements of Information Theory
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