Deep Learning for PDE-based Inverse Problems
Simon Arridge
University College London, London, UKPeter Maaß
Universität Bremen, Bremen, GermanyCarola-Bibiane Schönlieb
University of Cambridge, Cambridge, UK

Abstract
Analysing learned concepts for PDE-based parameter identification problems requires input from different research areas such as inverse problems, partial differential equations, statistics and mathematical foundations of deep learning. This workshop brought together a critical mass of experts in the various field. A thorough mathematical theory for PDE-based inverse problems using learned concepts is within reach in the coming few years and the inspiration of this Oberwolfach meeting will substantially influence this development.
Cite this article
Simon Arridge, Peter Maaß, Carola-Bibiane Schönlieb, Deep Learning for PDE-based Inverse Problems. Oberwolfach Rep. 21 (2024), no. 4, pp. 2805–2900
DOI 10.4171/OWR/2024/48