Variational Bayes learning of multiscale graphical models

Multiscale (multiresolution) graphical models have gained widespread popularity in recent years, since they enjoy rich modeling power as well as efficient inference procedures. Existing approaches to learning multiscale graphical models often leverage the framework of penalized likelihood, and therefore suffer from the issue of regularization selection. In… (More)