Solving inverse problems using data-driven models
University College London · University of Bremen · +2 more institutions
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Abstract
Recent research in inverse problems seeks to develop a mathematically coherent foundation for combining data-driven models, and in particular those based on deep learning, with domain-specific knowledge contained in physical–analytical models. The focus is on solving ill-posed inverse problems that are at the core of many challenging applications in the natural sciences, medicine and life sciences, as well as in engineering and industrial applications. This survey paper aims to give an account of some of the main contributions in data-driven inverse problems.
Citation impact
658
total citations
- FWCI
- 117.70
- Percentile
- 100%
- References
- 540
Citations per year
Authors
4Topics & keywords
Topics
Keywords
- Computer science
- Inverse problem
- Inverse
- Focus (optics)
- Domain (mathematical analysis)
- Data science
- Natural science
- Management science
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