Publications of the year 2026

Articles (2)

1. S. Banert, C. Brauer, D. Lorenz, L. Tondji.
   Why the noise model matters: a performance gap in learned regularization.
   Inverse Problems, , 2026.

   DOI: 10.1088/1361-6420/ae3f4c
   online at: https://arxiv.org/abs/2510.12521

2. F. Wiesener, T. Freudenberg, B. Bergmann, A. Rademacher, A. Schmidt, M. Eden, K. M. Heide.
   A multiscale simulation approach for grinding processes: grain engagement, heat generation, and coolant interaction.
   Production Engineering, 20:31 :1-19, Springer Verlag, 2026. published online

   DOI: 10.1007/s11740-025-01389-0

Preprints (2)

1. A. Behrens, M. Iske, M. Jiang, P. Maaß, S. Neumayer.
   A remark on an error analysis for classical and learned Tikhonov regularization schemes.
   Zur Veröffentlichung eingereicht.

   DOI: 10.48550/arXiv.2604.00759

2. L. Happ, S. Hendricks, C. M. Albrecht, L. Kaleschke, S. Patil, R. Fellegara, D. Lorenz.
   Advancing Sea Ice Surface Classification by Self-Supervised Contrastive Learning for Radar Altimetry.
   Zur Veröffentlichung eingereicht.

   DOI: 10.36227/techrxiv.176823164.49511515/v1