Title: Large scale computational inverse problems
Organizer(s): George Biros, Georgia Institute of Technology
Barbara Kaltenbacher, University of Graz, Austria
Speakers: Martin Benning, University of Munster, Germany
A linearized model for dynamic positron emission tomography

George Biros, Georgia Institute of Technology
Adaptive discretizations for the time harmonic inverse medium problem

Herbert Egger, Techical University of Chemnitz, Germany
On multilevel iterative solution of inverse problems

Thorsten Hohage, University of Gottingen, Germany
Large-scale inverse problems in photonic imaging

Youssef Marzouk, MIT
High-dimensional statistical inverse problems without Markov chains

John Schotland, University of Michigan
Inverse transport with large data sets

Christoph Schwarzbach, University of British Columbia, Canada
Inversion of electromagnetic data collected using a large number of sources

Georg Stadler, University of Texas at Austin
Global seismic full waveform inversion with quantified uncertainties
Abstract: An increasing demand for large scale inverse problems in many application domains (for example, seismic inversion, electromagnetic geophysical surveying, and novel high-resolution medical imaging technologies) has driven a significant growth in research efforts in the field of computational inverse problems. New methodologies have been developed to address scalability and robustness issues for large scale problems. Examples include multilevel strategies, adaptivity, and preconditioning. Also, a problem-specific development of efficient, tightly-coupled forward and inverse solvers often leads to successful methods for large scale applications. The aim of this minisymposium is to present recent trends in this field and provide a forum for exchange and discussion.

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