In this paper we propose two fast Total Variation (TV) based algorithms for image restoration by utilizing variational posterior distribution approximation. The unknown image and ...
Bruno Amizic, S. Derin Babacan, K. Michael Ng, Raf...
This paper addresses the problem of Voice Active Detection (VAD) in noisy environments. We introduce Variational Bayes approach to EM for classification to replace the heuristic ...
In this paper, we propose a symmetrical EEG/fMRI fusion algorithm which combines EEG and fMRI by means of a common generative model. The use of a total variation (TV) prior as wel...
Martin Luessi, S. Derin Babacan, Rafael Molina, Ja...
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
The purpose of this paper is to develop parameter transformation strategies that improve the accuracy of the Variational Bayes (VB) approximation. The idea is to find a transform...