Details

Autor(en) / Beteiligte

• Arridge, Simon
• Maass, Peter
• Öktem, Ozan
• Schönlieb, Carola-Bibiane

Titel

Solving inverse problems using data-driven models

Ist Teil von

• Acta numerica, 2019-05, Vol.28, p.1-174

Ort / Verlag

Cambridge, UK: Cambridge University Press

Erscheinungsjahr

2019

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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.