Solving inverse problems using data-driven models 论文

2019Acta Numerica引用 654
Numerical methods in inverse problemsSparse and Compressive Sensing TechniquesImage and Signal Denoising Methods

详细信息

发表期刊/会议
Acta Numerica
发表日期
2019-05-01
发表年份
2019

关键词

Numerical methods in inverse problemsSparse and Compressive Sensing TechniquesImage and Signal Denoising Methods

摘要

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.