Conference Agenda
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Statistical Inverse Problems Location: 0.002 Session Chair: Frank Werner | |
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Linear methods for non-linear inverse problems 1: Delft University of Technology; 2: Bocconi University, Italy We propose a novel Bayesian linearization approach for non-linear PDE constrained inverse problems. We split the non-linear inverse problem into a linear statistical and a non-linear analytic component. We derive optimal posterior contraction rates, reliable uncertainty quantification, data driven tuning and scalable approximations. The general approaches is applied to specific examples, including Darcy flow and heat equation with absorption term. | |
