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Monday, April 20, 2020 | History

2 edition of Convergence of Markov Chain Monte Carlo algorithms with applications to image restoration. found in the catalog.

Convergence of Markov Chain Monte Carlo algorithms with applications to image restoration.

Alison L. Gibbs

Convergence of Markov Chain Monte Carlo algorithms with applications to image restoration.

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  • 9 Currently reading

Published .
Written in English


The Physical Object
Pagination153 leaves.
Number of Pages153
ID Numbers
Open LibraryOL21692283M
ISBN 100612500039


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Convergence of Markov Chain Monte Carlo algorithms with applications to image restoration. by Alison L. Gibbs Download PDF EPUB FB2

Markov chain Monte Carlo (MCMC) algorithms, such as the Gibbs sampler, have provided a Bayesian inference machine in image analysis and in other areas of spatial statistics. Convergence Analysis of Markov Chain Monte Carlo Linear Solvers Using Ulam--von Neumann AlgorithmCited by: Download Citation | Convergence in the Wasserstein Metric for Markov Chain Monte Carlo Algorithms with Applications to Image Restoration |.

For example, the Large Step Markov Chain[10]relies on Markov chains to find convergence of many paths to form a global optimum and several papers cite Markov Chains as Author: Yan Bai. We prove an upper bound on the convergence rate of Markov Chain Monte Carlo (MCMC) algorithms for the important special case when the state space can be aggregated into a smaller space, such that.

Gibbs A L. Convergence in the Wasserstein metric for Markov chain Monte Carlo algorithms with applications to image restoration. Stoch Models,20(4): – MathSciNetAuthor: Neng-Yi Wang.