Manuscript Topics

Inverse problems have become increasingly important in various scientific and engineering fields, including medical imaging, geophysics, and non-destructive testing, among others. Machine learning methods have been shown to be effective in solving inverse problems, particularly when the underlying physics of the problem is complex and difficult to model. This special issue aims to showcase recent advances in the application of inverse problems and machine learning to solve problems in various areas of science and technology. We welcome contributions on theoretical and computational aspects of inverse problems, as well as novel applications in areas such as medical imaging, geophysics, material science, health monitoring, and more.

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