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Personal profile

Research interests

Inverse Problems


Machine Learning


Education/Academic qualification

Medical Imaging, Doctor of Philosophy, University College London

May 2012Apr 2015

Industrial Mathematics, Master of Science, Universität Bremen

Sep 2006Jan 2012


  • Inverse Problems
  • Imaging
  • Machine Learning
  • Optimization
  • Medical Imaging
  • Applied Mathematics

Fingerprint Dive into the research topics where Matthias Ehrhardt is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Machine Learning Mathematics
Inverse Problem Mathematics
Imaging Mathematics
Optimization Mathematics

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Projects 2019 2023

Research Output 2012 2019

  • 12 Article
  • 7 Working paper
  • 5 Conference contribution

Deep learning as optimal control problems: models and numerical methods

Benning, M., Celledoni, E., Ehrhardt, M. J., Owren, B. & Schönlieb, C-B., 11 Apr 2019, arXiv.

Research output: Working paper

3 Downloads (Pure)

Enhancing joint reconstruction and segmentation with non-convex Bregman iteration

Corona, V., Benning, M., Ehrhardt, M. J., Gladden, L. F., Mair, R., Reci, A., Sederman, A. J., Reichelt, S. & Schoenlieb, C-B., 26 Apr 2019, In : Inverse Problems. 35, 5, 34 p., 055001.

Research output: Contribution to journalArticle

Open Access

Faster PET reconstruction with non-smooth priors by randomization and preconditioning

Ehrhardt, M. J., Markiewicz, P. J. & Schönlieb, C-B., 20 Aug 2019, In : Physics in Medicine and Biology.

Research output: Contribution to journalArticle

Open Access

Incorporating structural prior information and sparsity into EIT using parallel level sets

Kolehmainen, V., Ehrhardt, M. J. & Arridge, S. R., 31 Jan 2019, In : Inverse Problems and Imaging. 13, 2, p. 285-307 23 p.

Research output: Contribution to journalArticle

Open Access

Learning the Sampling Pattern for MRI

Sherry, F., Benning, M., Reyes, J. C. D. L., Graves, M. J., Maierhofer, G., Williams, G., Schönlieb, C-B. & Ehrhardt, M. J., 20 Jun 2019.

Research output: Working paper