Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model
Tanaka, Kazuyuki, Nakamura, Masamichi, Kataoka, Shun, Ohzeki, Masayuki, Yasuda, Muneki
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.
artificial intelligence, bayesian inference, momentum-space renormalization group transformation, (8 more...)
Mar-19-2018