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» Coarse-to-Fine Statistical Shape Model by Bayesian Inference
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ICML
2009
IEEE
15 years 10 months ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
RECOMB
2003
Springer
15 years 10 months ago
Optimizing exact genetic linkage computations
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...
Dan Geiger, Maáyan Fishelson
BIBE
2007
IEEE
132views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study
—A computational framework is presented for surface based morphometry to localize shape changes between groups of 3D objects. It employs the spherical harmonic (SPHARM) method fo...
Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huan...
ICASSP
2009
IEEE
14 years 7 months ago
Robust Bayesian tracking on Riemannian manifolds via fragments-based representation
Recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. It enables efficient fusion of different types of features. Ba...
Yi Wu, Jinqiao Wang, Hanqing Lu
SIAMSC
2011
219views more  SIAMSC 2011»
14 years 4 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...