Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model
Tohoku University（东北大学）；Yamagata University（山形大学）
英文摘要：
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.
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