Dr. Matthias Beckmann

Courses (Selection)complete list

1. Mathematical Methods in Machine Learning (Wintersemester 2024/2025)
2. Advanced Topics in Image Processing – The Beauty of Variational Calculus (Wintersemester 2024/2025)
3. Mathematical Foundations of Machine Learning (Sommersemester 2024)
4. Mathematical Foundations of Machine Learning (Sommersemester 2023)
5. Inverse Problems (Wintersemester 2022/2023)

Theses (Selection)complete list

1. Inversion of the Modulo Radon Transform via Laplacian Phase Unwrapping (Carla Dittert)
2. The Radon Cumulative Distribution Transform in Image Classification (Lia Pribnow)
3. Inversion of the Modulo Radon Transform via direct Fourier Reconstruction Methods (Meira Iske)
4. Equivariant Neural Networks for Indirect Measurements (Nick Heilenkötter)
5. Approximation nichtlinearer Operatoren durch Neuronale Netze und ihre Implementierung durch DeepONets (Theresa Sauerland)

Publications (Selection)complete list

1. M. Beckmann, N. Heilenkötter.
   Equivariant Neural Networks for Indirect Measurements.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2306.16506

2. M. Beckmann, A. Bhandari, M. Iske.
   Fourier-Domain Inversion for the Modulo Radon Transform.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2307.13114

3. M. Beckmann, A. Bhandari, F. Krahmer.
   The Modulo Radon Transform: Theory, Algorithms and Applications.
   SIAM Journal on Imaging Sciences, 15(2):455-490, 2022.

   DOI: 10.1137/21M1424615

4. M. Beckmann, A. Bhandari.
   MR. TOMP: Inversion of the Modulo Radon Transform (MRT) via Orthogonal Matching Pursuit (OMP).
   2022 IEEE International Conference on Image Processing (ICIP), 16.10.-19.10.2022.
   
5. M. Beckmann, P. Maaß, J. Nickel.
   Error analysis for filtered back projection reconstructions in Besov spaces.
   Inverse Problems, 37 014002 37(1), IOPscience, 2020.