Publikationen der AG Inverse Probleme und Bildverarbeitung

Zeitschriftenartikel (8)

1. S. Banert, O. Öktem, J. Adler, J. Rudzusika.
   Accelerated Forward-Backward Optimization using Deep Learning.
   Erscheint in SIAM Journal on Optimization

   online unter: https://arxiv.org/abs/2105.05210

2. D. Lorenz, F. Schneppe.
   Chambolle-Pock’s primal-dual method with mismatched adjoint.
   Applied Mathematics & Optimization, 87(22), 2023.

   DOI: 10.1007/s00245-022-09933-5
   online unter: https://arxiv.org/abs/2201.04928

3. N. K. Bellam Muralidhar, C. Gräßle, N. Rauter, A. Mikhaylenko, R. Lammering, D. Lorenz.
   Damage identification in fiber metal laminates using bayesian analysis with model order reduction.
   Computer Methods in Applied Mechanics and Engineering, Part B 403, 2023.

   DOI: 10.1016/j.cma.2022.115737
   online unter: https://arxiv.org/abs/2206.04329

4. D. Nganyu Tanyu, J. Ning, T. Freudenberg, N. Heilenkötter, A. Rademacher, U. Iben, P. Maaß.
   Deep learning methods for partial differential equations and related parameter identification problems.
   Inverse Problems, 39(10), 2023.

   DOI: 10.1088/1361-6420/ace9d4

5. S. Banert, P. Giselsson, H. Sadeghi.
   Incorporating history and deviations in forward–backward splitting.
   Numerical Algorithms, , 2023.

   DOI: 10.1007/s11075-023-01686-8

6. D. Lorenz, F. Schneppe, L. Tondji.
   Linearly convergent adjoint free solution of least squares problems by random descent.
   Inverse Problems, 39(12), 125019, 2023.

   DOI: 10.1088/1361-6420/ad08ed
   online unter: https://arxiv.org/abs/2306.01946

7. S. Banert, P. Giselsson, M. Morin.
   Nonlinear Forward-Backward Splitting with Momentum Correction.
   Set-Valued and Variational Analysis, 31(37), 2023.

   DOI: 10.1007/s11228-023-00700-4

8. A. Ebner, J. Frikel, D. Lorenz, J. Schwab, M. Haltmeier.
   Regularization of inverse problems by filtered diagonal frame decomposition.
   Applied and Computational Harmonic Analysis, 62:66-83, 2023.

   DOI: 10.1016/j.acha.2022.08.005
   online unter: https://arxiv.org/abs/2008.06219

Tagungsbeiträge (1)

1. L. Tondji, D. Lorenz, I. Necoara.
   An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization.
   2023 European Control Conference (ECC).
   

   DOI: 10.23919/ECC57647.2023.10178390

Preprints (2)

1. D. Nganyu Tanyu, J. Ning, A. Hauptmann, B. Jin, P. Maaß.
   Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2310.18636

2. D. Lorenz, M. Winkler.
   Minimal error momentum Bregman-Kaczmarz.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2307.15435