Inverse Problem in Pairwise Markov Random Fields Using Loopy Belief Propagation

Abstract

In this paper, using Chebyshev polynomials, we derive a new representation of loopy belief propagation for pairwise Markov random fields in terms of moments. Using the new representation, we propose a new method to solve a statistical inverse problem in pairwise Markov random fields within the framework of loopy belief propagation. Our method allows us to solve the statistical inverse problem without any iterative operations. We numerically verify our method for the statistical inverse problem in Q -state Potts models.