Learning Approaches for PDE Forward and Inverse Problems
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Organizer(s): |
Name:
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Affiliation:
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Country:
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Kui Ren
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Columbia University
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USA
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Introduction:
| | Ideas and methodologies originating from machine learning have penetrated deeply into applied mathematics research in the past several years, resulting in the coupling of traditional physics-based modeling with the emerging data-driven modeling approaches of applied mathematics. In particular, various machine learning methods have been developed for solving forward and inverse problems of partial differential equations. This session intends to highlight recent advances in this fascinating research area.
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