Susceptibility Propagation by Using Diagonal Consistency

Abstract

A susceptibility propagation that is constructed by combining a belief propagation and a linear response method is used for approximate computation for Markov random fields. Herein, we formulate a new, improved susceptibility propagation by using the concept of a diagonal matching method that is based on mean-field approaches to inverse Ising problems. The proposed susceptibility propagation is robust for various network structures, and it is reduced to the ordinary susceptibility propagation and to the adaptive Thouless-Anderson-Palmer equation in special cases.

References in corpus (2)

• Tractable approximations for probabilistic models: The adaptive TAP mean field approach
• Intrinsic limitations of inverse inference in the pairwise Ising spin glass

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