Dr. Matthias Beckmann

Courses (Selection)complete list

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

Theses (Selection)complete list

1. Generalized Modulo Operators and Recovery Approaches for the Induced Modulo Radon Transform (Jürgen Jeschke)
2. Learned Postprocessing Methods for Inverse Problems in the Context of Magnetic Particle Imaging (Tom Bustert)
3. Inversion of the Modulo Radon Transform via Laplacian Phase Unwrapping (Carla Dittert)
4. The Radon Cumulative Distribution Transform in Image Classification (Lia Pribnow)
5. Inversion of the Modulo Radon Transform via direct Fourier Reconstruction Methods (Meira Iske)

Publications (Selection)complete list

1. M. Beckmann, J. Jeschke.
   Generalized Modulo Hysteresis Encoding.
   Erscheint in IEEE Transactions on Information Theory

   DOI: 10.1109/TIT.2026.3744276
   online at: https://arxiv.org/abs/2608.01270

2. M. Beckmann, J. Jeschke.
   Orthogonal Matching Pursuit based Reconstruction for Modulo Hysteresis Operators.
   2025 International Conference on Sampling Theory and Applications (SampTA)}, IEEE, 2025.

   DOI: 10.1109/SampTA64769.2025.11133522

3. M. Beckmann, J. Nickel.
   Optimized filter functions for filtered back projection reconstructions.
   Inverse Problems and Imaging, , 2025.

   DOI: 10.3934/ipi.2025003

4. D. Hauser, M. Beckmann, G. Koliander, H. S. Stiehl.
   On Image Processing and Pattern Recognition for Thermograms of Watermarks in Manuscripts - A First Proof-of-Concept.
   18th International Conference on Document Analysis and Recognition (ICDAR), 30.08.-04.09.2024.
   

   DOI: 10.1007/978-3-031-70543-4_6

5. M. Beckmann, N. Heilenkötter.
   Equivariant Neural Networks for Indirect Measurements.
   SIAM Journal on Mathematics of Data Science, 6(3), 2024.

   DOI: 10.1137/23M1582862
   online at: https://epubs.siam.org/doi/10.1137/23M1582862