2023
DOI: 10.21203/rs.3.rs-2713062/v1
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Solving inverse problems with sparse noisy data, operator splitting and physics-constraints machine learning

Abstract: Using measurable data as a starting point, inverse problems can be used to estimate model parameters. In science and engineering, several problems can be viewed as inverse problems. Partial differential equations (PDEs) or variational problems are also used to characterize similar issues. Typically, an energy function is used to address a variational problem. Because curvature-driven regularities have been shown to require a lot of prior understanding of physics concepts, they have received a lot of attention.… Show more

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