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This paper presents an improved implicit sampling method for hierarchical Bayesian inverse problems. A widely used approach for sampling posterior distribution is based on Markov chain Monte Carlo (MCMC). However, the samples generated by MCMC are us
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a71812605e73a303cee11cd11338eeb