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» Variational Inference for Diffusion Processes
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ICASSP
2009
IEEE
14 years 2 months ago
Structured variational methods for distributed inference in wireless ad hoc and sensor networks
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
Yanbing Zhang, Huaiyu Dai
JMLR
2010
129views more  JMLR 2010»
13 years 2 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
ICIP
2006
IEEE
14 years 9 months ago
Robust Anisotropic Disparity Estimation with Perceptual Maximum Variation Modeling
We present a robust anisotropic dense disparity estimation algorithm which employs perceptual maximum variation modeling. Edge-preserving dense disparity vectors are estimated usi...
Jangheon Kim, Thomas Sikora
IJDMB
2010
61views more  IJDMB 2010»
13 years 5 months ago
On a novel coalescent model for genome-wide evolution of Copy Number Variations
: Since we are limited in our knowledge of human demographic history and variations of recombination and mutation rates, large-scale computer simulation is a necessary tool in gene...
Antonina Mitrofanova, Bhubaneswar (Bud) Mishra
ICIP
2001
IEEE
14 years 9 months ago
Variable-conductance, level-set curvature for image denoising
This paper describes a partial differential equation for denoising images. The proposed method is demonstrably superior to anisotropic diffusion (and it's many variations) fo...
Ross T. Whitaker, Xinwei Xue