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Learn advanced techniques for solving inverse scattering problems through a workshop presentation that explores multi-frequency progressive refinement methods enhanced by machine learning approaches. Discover how to systematically improve reconstruction quality by leveraging multiple frequency components in scattering data, with particular focus on computational strategies that progressively refine solutions. Examine the mathematical foundations underlying inverse scattering theory and understand how modern learning algorithms can be integrated to overcome traditional limitations in reconstruction accuracy and computational efficiency. Explore practical applications of these methods in various fields including medical imaging, geophysical exploration, and materials characterization, while gaining insights into the latest research developments in computational inverse problems from a leading expert in the field.
