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Dr. Matthias Beckmann

Wissenschaftlicher Mitarbeiter der AG Technomathematik

Raum: MZH 2260
E-Mail: matthias.beckmann@uni-bremen.de
Telefon: (0421) 218-63810

Veranstaltungen (Auswahl)vollständige Liste

  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)

Abschlussarbeiten (Auswahl)vollständige Liste

  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)

Publikationen (Auswahl)vollständige Liste

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

    DOI: 10.3934/ipi.2025003

  2. 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 unter: https://epubs.siam.org/doi/10.1137/23M1582862

  3. M. Beckmann, A. Bhandari, M. Iske.
    Fourier-Domain Inversion for the Modulo Radon Transform.
    IEEE Transactions on Computational Imaging, 10, 2024.

    online unter: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10499837

  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, 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