Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model
Machine Learning
2018-08-01 v1 Statistical Mechanics
Machine Learning
Abstract
A new Bayesian modeling method is proposed by combining the maximization of the marginal likelihood with a momentum-space renormalization group transformation for Gaussian graphical models. Moreover, we present a scheme for computint the statistical averages of hyperparameters and mean square errors in our proposed method based on a momentumspace renormalization transformation.
Cite
@article{arxiv.1804.00727,
title = {Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model},
author = {Kazuyuki Tanaka and Masamichi Nakamura and Shun Kataoka and Masayuki Ohzeki and Muneki Yasuda},
journal= {arXiv preprint arXiv:1804.00727},
year = {2018}
}
Comments
6 pages, 1 figure