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» Density Estimation by Mixture Models with Smoothing Priors
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ISBI
2008
IEEE
14 years 9 months ago
Robust maximum likelihood estimation in Q-space MRI
Q-space imaging is an emerging diffusion weighted MR imaging technique to estimate molecular diffusion probability density functions (PDF's) without the need to assume a Gaus...
Bennett A. Landman, Jonathan A. D. Farrell, Seth A...
ESANN
2004
13 years 10 months ago
Robust Bayesian Mixture Modelling
Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previou...
Christopher M. Bishop, Markus Svensén
JCST
2010
139views more  JCST 2010»
13 years 7 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen
ICPR
2008
IEEE
14 years 9 months ago
Kernel bandwidth estimation in methods based on probability density function modelling
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
Adrian G. Bors, Nikolaos Nasios
ITCC
2003
IEEE
14 years 1 months ago
Cluster-Weighted Modeling as a basis for Fuzzy Modeling
The Cluster-Weighted Modeling (CWM) is emerging as a versatile tool for modeling dynamical systems. It is a mixture density estimator around local models. To be specific, the inpu...
Madasu Hanmandlu, Vamsi Krishna Madasu, Shantaram ...