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» Bayesian Approaches to Gaussian Mixture Modeling
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TMI
2010
175views more  TMI 2010»
13 years 3 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
ARTMED
2004
118views more  ARTMED 2004»
13 years 9 months ago
Bayesian fluorescence in situ hybridisation signal classification
Previous research has indicated the significance of accurate classification of fluorescence in situ hybridisation (FISH) signals for the detection of genetic abnormalities. Based ...
Boaz Lerner
UAI
2001
13 years 10 months ago
Expectation Propagation for approximate Bayesian inference
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
Thomas P. Minka
ISMB
2001
13 years 10 months ago
Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences
Accurately estimating probabilities from observations is important for probabilistic-based approaches to problems in computational biology. In this paper we present a biologically...
Eleazar Eskin, William Noble Grundy, Yoram Singer
LION
2009
Springer
129views Optimization» more  LION 2009»
14 years 3 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...