A path integral approach to Bayesian inference in Markov processes

Published 21 Oct 2017 in math.ST, cond-mat.stat-mech, and stat.TH | (1710.07755v1)

Abstract: We formulate Bayesian updates in Markov processes by means of path integral techniques and derive the imaginary-time Schr\"{o}dinger equation with likelihood to direct the inference incorporated as a potential for the posterior probability distribution

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