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SUMMARY:Convergence Rates for Bayesian Inversion - Hanne Kekkonen (Univers
 ity of Helsinki)
DTSTART:20160512T140000Z
DTEND:20160512T150000Z
UID:TALK65863@talks.cam.ac.uk
CONTACT:Carola-Bibiane Schoenlieb
DESCRIPTION:Let us consider an indirect noisy measurement M of a physical 
 quantity M = AU + delta E where the measurement M\, noise E and the unknow
 n U are treated as random variables and delta models the noise amplitude. 
 We are interested to know what happens to the approximate solution of abov
 e when delta -> 0. The analysis of small noise limit\, also known as the t
 heory of posterior consistency\, has attracted a lot of interest in the la
 st decade\, however\, much remains to be done. Developing a comprehensive 
 theory is important since posterior consistency justifies the use of Bayes
 ian approach the same way as convergence results do\nthe use of regularisa
 tion techniques.
LOCATION:MR 14\, CMS
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