Judith Nickel

Publications (Selection)complete list

1. 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.
   Zur Veröffentlichung eingereicht.

   online at: https://www.x-mol.net/paper/article/1682514725633245184

2. 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 at: https://iopscience.iop.org/article/10.1088/1361-6420/ad0660

3. 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

4. C. Arndt, A. Denker, J. Nickel, J. Leuschner, M. Schmidt, G. Rigaud.
   In Focus - hybrid deep learning approaches to the HDC2021 challenge.
   Inverse Problems and Imaging, , 2022.

   DOI: 10.3934/ipi.2022061

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.