Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...
Abstract. The label switching problem, the unidentifiability of the permutation of clusters or more generally latent variables, makes interpretation of results computed with MCMC ...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...