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ICIP
2008
IEEE
14 years 6 months ago
Variational Bayesian image processing on stochastic factor graphs
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...
Xin Li
TIP
2011
231views more  TIP 2011»
12 years 11 months ago
Variational Bayesian Super Resolution
—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...
DATE
2007
IEEE
92views Hardware» more  DATE 2007»
13 years 11 months ago
Random sampling of moment graph: a stochastic Krylov-reduction algorithm
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...
Zhenhai Zhu, Joel R. Phillips
NIPS
2008
13 years 6 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
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...
Shenghuo Zhu, Kai Yu, Yihong Gong
INFFUS
2010
143views more  INFFUS 2010»
13 years 3 months ago
A multi-agent systems approach to distributed bayesian information fusion
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...