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» Bayesian Parameter Estimation: A Monte Carlo Approach
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JCB
2007
198views more  JCB 2007»
13 years 10 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
ICCV
2003
IEEE
15 years 24 days ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
BIBE
2008
IEEE
203views Bioinformatics» more  BIBE 2008»
14 years 5 months ago
A study of the parameters affecting minimum detectable activity concentration level of clinical LSO PET scanners
— Recent studies in the field of molecular imaging have demonstrated the need for PET probes capable of imaging very weak activity distributions. Over this range of applications ...
Nicolas A. Karakatsanis, Konstantina S. Nikita
JMLR
2011
148views more  JMLR 2011»
13 years 5 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
ICML
2009
IEEE
14 years 11 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...