We propose a method to improve approximate inference methods by correcting for the influence of loops in the graphical model. The method is a generalization and alternative implem...
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Accurate noise level estimation is essential to assure good performance of noise reduction filters. Noise contaminating raw images is typically modeled as additive white and Gauss...
Angelo Bosco, Arcangelo Bruna, D. Giacalone, Sebas...
It has been demonstrated that basic aspects of human visual motion perception are qualitatively consistent with a Bayesian estimation framework, where the prior probability distri...