Abstract--In this paper, we (1) provide a complete framework for classification using Variational Mixture of Experts (VME); (2) derive the variational lower bound; and (3) apply th...
Abstract. We propose an algorithmic framework for computing global solutions of variational models with convex regularity terms that permit quite arbitrary data terms. While the mi...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
We study a notion of variation for real valued two variable functions called the path variation and we discuss its application as a low-level image segmentation method. For this pu...
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
In this paper we present a continuous surface model to describe the interconnect geometric variation, which improves the currently used model for better accuracy while not increas...