【摘 要】
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We formulate an A-optimal experimental design criterion for infinitedimensional nonlinear Bayesian inverse problems.Our method aims to minimize the average variance of a Gaussian approximation to post
【机 构】
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The Univ.of Texas at Austin
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We formulate an A-optimal experimental design criterion for infinitedimensional nonlinear Bayesian inverse problems.Our method aims to minimize the average variance of a Gaussian approximation to posterior law of inversion parameters by solving a bi-level PDE-constrained optimization problem.I will also discuss risk-averse optimization under uncertainty with application to optimal control of PDEs with uncertain parameter fields.We use numerical results for a porous medium flow problem with uncertain permeability to illustrate the methods.
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