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SUMMARY:Modes of posterior measure for Bayesian inverse problems with a cl
 ass of non-Gaussian priors - Masoumeh Dashti (University of Sussex)
DTSTART:20180412T090000Z
DTEND:20180412T093000Z
UID:TALK103705@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:We consider the inverse problem of recovering an unknown funct
 ional parameter from noisy and indirect observations. We adopt a Bayesian 
 approach and\, for a non-smooth\, non-Gaussian and sparsity-promoting clas
 s of prior measures\, show that maximum a posteriori (MAP) estimates are c
 haracterized by the minimizers of a generalized Onsager-Machlup functional
  of the posterior. We also discuss some posterior consistency results. Thi
 s is based on joint works with S. Agapiou\, M.Burger and T. Helin.
LOCATION:Seminar Room 1\, Newton Institute
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