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• W1989981036 abstract "Abstract We study empirical and hierarchical Bayes approaches to the problem of estimating an infinite-dimensional parameter in mildly ill-posed inverse problems. We consider a class of prior distributions indexed by a hyperparameter that quantifies regularity. We prove that both methods we consider succeed in automatically selecting this parameter optimally, resulting in optimal convergence rates for truths with Sobolev or analytic “smoothness”, without using knowledge about this regularity. Both methods are illustrated by simulation examples." @default.
• W1989981036 created "2016-06-24" @default.
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• W1989981036 date "2015-02-22" @default.
• W1989981036 modified "2023-10-16" @default.
• W1989981036 title "Bayes procedures for adaptive inference in inverse problems for the white noise model" @default.
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• W1989981036 doi "https://doi.org/10.1007/s00440-015-0619-7" @default.
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