Gaussian measure

Friday, September 8, 2017 - 9:35am - 10:10am
Tan Bui-Thanh (The University of Texas at Austin)
We cast data assimilation problem into a model inadequacy problem which is then solved by a Bayesian approach. The Bayesian posterior is then used for Bayesian Optimal Experimental Design (OED). Our focus is on the A- and D-optimal OED problems for which we construct scalable approximations that involve: 1) randomized trace estimators; 2) Gaussian quadratures; and 3) trace upper bounds. Unlike most of contemporary approaches, our methods work directly with the inverse of the posterior covariance, i.e.
Monday, March 14, 2016 - 4:30pm - 5:00pm
Omar Ghattas (The University of Texas at Austin)
We present methods for the optimal control of systems governed by partial differential equations with an infinite-dimensional uncertain parameter field. We consider an objective function that involves the mean
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