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» Robust Bayesian Mixture Modelling
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DSP
2007
13 years 7 months ago
Variational and stochastic inference for Bayesian source separation
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Ali Taylan Cemgil, Cédric Févotte, S...
CSDA
2010
165views more  CSDA 2010»
13 years 7 months ago
A two-component Weibull mixture to model early and late mortality in a Bayesian framework
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
Alessio Farcomeni, Alessandra Nardi
PAMI
1998
94views more  PAMI 1998»
13 years 7 months ago
Bayesian Approaches to Gaussian Mixture Modeling
—A Bayesian-based methodology is presented which automatically penalizes overcomplex models being fitted to unknown data. We show that, with a Gaussian mixture model, the approac...
Stephen J. Roberts, Dirk Husmeier, Iead Rezek, Wil...
CSDA
2007
151views more  CSDA 2007»
13 years 7 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
MICCAI
2008
Springer
14 years 8 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...