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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Detalles Bibliográficos
Autores principales: Marnissi, Yosra, Chouzenoux, Emilie, Benazza-Benyahia, Amel, Pesquet, Jean-Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512603/
https://www.ncbi.nlm.nih.gov/pubmed/33265201
http://dx.doi.org/10.3390/e20020110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512603/
https://www.ncbi.nlm.nih.gov/pubmed/33265201
http://dx.doi.org/10.3390/e20020110

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