BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Surrogate models in Bayesian Inverse Problems - Aretha  Teckentrup
  (University of Edinburgh)
DTSTART:20180208T113000Z
DTEND:20180208T123000Z
UID:TALK100210@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Co-authors: Andrew Stuart		(Caltech)    \, Han Cheng Lie
  and Timm Sullivan (Free University Berlin)    <br></span><span><br>We are
  interested in the inverse problem of estimating unknown parameters in a m
 athematical model from observed data. We follow the Bayesian approach\, in
  which the solution to the inverse problem is the probability distribution
  of the unknown parameters conditioned on the observed data\, the so-calle
 d posterior distribution. We are particularly interested in the case where
  the mathematical model is non-linear and expensive to simulate\, for exam
 ple given by a partial differential equation. We consider the use of surro
 gate models to approximate the Bayesian posterior distribution. We present
  a general framework for the analysis of the error introduced in the poste
 rior distribution\, and discuss particular examples of surrogate models su
 ch as Gaussian process emulators and randomised misfit approaches.</span>
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR