Clemens Arndt

Bild Clemens Arndt

Clemens Arndt

Wissenschaftlicher Mitarbeiter

Doktorand
Team Deep Learning und Inverse Probleme

Bibliothekstraße 5
28359 Bremen

Raum: MZH 2300
Telefon: +49 421 218-63808
E-Mail: carndtprotect me ?!uni-bremenprotect me ?!.de

Forschungsgebiete

  • Deep Learning
  • Inverse Probleme

 

Zeitschriftenartikel

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.
DOI: 10.1088/1361-6420/ac9011

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

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), 2023.
DOI: 10.1088/1361-6420/ad0660
 

Preprints

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