In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
—In this paper, we address the super resolution (SR) problemfromasetofdegradedlowresolution(LR)imagestoobtain a high resolution (HR) image. Accurate estimation of the sub-pixel m...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
In this paper we introduce a new algorithm for model order reduction in the presence of parameter or process variation. Our analysis is performed using a graph interpretation of t...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...