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» On Bayesian model and variable selection using MCMC
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TASLP
2002
109views more  TASLP 2002»
14 years 9 months ago
Particle methods for Bayesian modeling and enhancement of speech signals
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, S...
70
Voted
IDA
2009
Springer
15 years 4 months ago
Bayesian Solutions to the Label Switching Problem
Abstract. The label switching problem, the unidentifiability of the permutation of clusters or more generally latent variables, makes interpretation of results computed with MCMC ...
Kai Puolamäki, Samuel Kaski
CSDA
2011
14 years 4 months ago
Mapping electron density in the ionosphere: A principal component MCMC algorithm
The outer layers of the Earth’s atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere var...
Eman Khorsheed, Merrilee Hurn, Christopher Jenniso...
ICIP
1999
IEEE
15 years 11 months ago
Uncertainties in Bayesian Geometric Models
Deformable geometric models fit very naturally into the context of Bayesian analysis. The prior probability of boundary shapes is taken to proportional to the negative exponential...
Kenneth M. Hanson, Gregory S. Cunningham, Robert J...
101
Voted
IPPS
2008
IEEE
15 years 4 months ago
Reducing the run-time of MCMC programs by multithreading on SMP architectures
The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Mont...
Jonathan M. R. Byrd, Stephen A. Jarvis, A. H. Bhal...