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Learning Regularization for Inverse Problems, Take 2

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DDEW03 - Computational Challenges and Emerging Tools

The idea of using learning techniques for inverse problems is not new, and is strongly connected to the area of empirical Baye’s. However, in the last few years new techniques have emerged that enebale us to learn from a vast amout of a-priori data. In this talk we will review the field, the new methods and the challenges the field is facing. We also propose new regularization functionals that are easy to learn and use.

This talk is part of the Isaac Newton Institute Seminar Series series.

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Rooms SG1 & SG2, Alison Richard Building, 7 West Road, Cambridge, CB3 9DT Cambridge University Physics Society (CUPS) 2025-2026 Talks Large Lecture Theatre, Department of Geography

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