Dr. Clemens Arndt
Wissenschaftlicher Mitarbeiter der AG TechnomathematikPublikationen (Auswahl)
- C. Arndt, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, J. Nickel.
Bayesian view on the training of invertible residual networks for solving linear inverse problems.
Inverse Problems, 40 045021 40(4), IOPscience, 2024.DOI: 10.1088/1361-6420/ad2aaa
online unter: https://www.x-mol.net/paper/article/1682514725633245184 - C. Arndt, J. Nickel.
Invertible ResNets for inverse imaging problems: Competitive performance with provable regularization properties.
Zur Veröffentlichung eingereicht.online unter: https://arxiv.org/abs/2409.13482
- C. Arndt, A. Denker, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, P. Maaß, J. Nickel.
Invertible residual networks in the context of regularization theory for linear inverse problems.
Inverse Problems, 39(12), IOPscience, 2023.DOI: 10.1088/1361-6420/ad0660
online unter: https://iopscience.iop.org/article/10.1088/1361-6420/ad0660 - C. Arndt, A. Denker, S. Dittmer, J. Leuschner, J. Nickel, M. Schmidt.
Model-based deep learning approaches to the Helsinki Tomography Challenge 2022.
Applied Mathematics for Modern Challenges, 1(2), 2023.DOI: 10.3934/ammc.2023007
- C. Arndt.
Regularization Theory of the Analytic Deep Prior Approach.
Inverse Problems, 38(11), 2022.