A path integral approach to Bayesian inference in Markov processes
Statistics Theory
2017-10-24 v1 Statistical Mechanics
Statistics Theory
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
Keywords
Cite
@article{arxiv.1710.07755,
title = {A path integral approach to Bayesian inference in Markov processes},
author = {Toshiyuki Fujii and Noriyuki Hatakenaka},
journal= {arXiv preprint arXiv:1710.07755},
year = {2017}
}
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13 pages