Automatic Tempered Posterior Distributions for Bayesian Inversion Problems
We propose a novel adaptive importance sampling scheme for Bayesian inversion problems where the inference of the variables of interest and the power of the data noise are carried out using distinct (but interacting) methods. More specifically, we consider a Bayesian analysis for the variables of in...
Main Authors: | Luca Martino, Fernando Llorente, Ernesto Curbelo, Javier López-Santiago, Joaquín Míguez |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-04-01
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Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/9/7/784 |
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