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DESCRIPTION:Formulation and solution of stochastic inverse problems for sci
 ence and engineering models\n\n \n\n\n	Abstract:\n\n\nThe stochastic invers
 e problem of determining probability structures on input parameters for a 
 physics model corresponding to a given probability structure on the output
  of the model forms the core of scientific inference and engineering desig
 n. We describe a formulation and solution method for stochastic inverse pr
 oblems that is based on functional analysis\, differential geometry\, and 
 probability/measure theory. This approach yields a computationally tractab
 le problem while avoiding alterations of the model like regularization and
  ad hoc assumptions about the probability structures. We present several e
 xamples\, including a high-dimensional application to determination of par
 ameter fields in storm surge models. We also describe work aimed at defini
 ng a notion of condition for stochastic inverse problems and tackling the 
 related problem of designing sets of optimal observable quantities.\n\n\n	S
 peaker\n\n\nDon Estep is the Director of CANSSI and a professor in the Dep
 artment of Statistics and Actuarial Science at Simon Fraser University. Pr
 eviously\, he was a University Distinguished Professor\, University Interd
 isciplinary Research Scholar\, and Chair of the Department of Statistics a
 t Colorado State University. Before that\, he was a professor in the Schoo
 l of Mathematics at Georgia Tech for 13 years. He has also spent significa
 nt amounts of time at Chalmers University of Technology in Göteborg\, Swed
 en and Caltech.\n
DTSTART:20191122T210000Z
DTEND:20191122T220000Z
LOCATION:Room PK-5115 \, CA\, Pavillon President-Kennedy
SUMMARY:Professor Don Estep (Simon Fraser University)
URL:/mathstat/channels/event/professor-don-estep-simon
 -fraser-university-302751
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