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An Auxiliary Variable Method for Markov Chain Monte Carlo Algorithms in High Dimension
In this paper, we are interested in Bayesian inverse problems where either the data fidelity term or the prior distribution is Gaussian or driven from a hierarchical Gaussian model. Generally, Markov chain Monte Carlo (MCMC) algorithms allow us to generate sets of samples that are employed to infer...
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| Vydáno v: | Entropy (Basel) |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI
2018
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7512603/ https://ncbi.nlm.nih.gov/pubmed/33265201 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e20020110 |
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