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Publikationen des Jahres 2026

Zeitschriftenartikel (7)

  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 unter: https://arxiv.org/abs/2510.12521

  2. J. Bresch, D. Lorenz, F. Schneppe, M. Winkler.
    Computing adjoint mismatch of linear maps.
    Journal of Computational and Applied Mathematics, 488, 117853, 2026.

    DOI: 10.1016/j.cam.2026.117853
    online unter: https://arxiv.org/abs/2503.21361

  3. J. Bresch, D. Lorenz, F. Schneppe, M. Winkler.
    Matrix-free stochastic calculation of operator norms without using adjoints.
    SIAM Journal on Matrix Analysis and Applications, 47(3):1349--137, SIAM, 2026.

    DOI: 10.1137/25M1772277
    online unter: https://epubs.siam.org/doi/full/10.1137/25M1772277

  4. G. Kuhlmann, L. Langenhorst, M. Knauer, N. Guba, T. Hüsemann, C. Heinzel.
    Investigation of Surface Integrity Changes in Multistage Grinding with Interim Thermally Induced Material Modifications.
    Procedia CIRP, 144:55-60, 2026.

    DOI: 10.1016/j.procir.2026.02.095

  5. D. Lorenz, M. Winkler, A. Leitão, J. C. Rabelo.
    On inertial Levenberg-Marquardt type methods for solving nonlinear ill-posed operator equations.
    IMA Journal of Numerical Analysis, , Oxford University Press, 2026.

    DOI: 10.1093/imanum/drag017
    online unter: https://arxiv.org/abs/2406.07044

  6. F. Schneppe, E. Naldi.
    The Influence of an Adjoint Mismatch on the Primal-Dual Douglas-Rachford Method.
    Optimization, , 1–38 S., Taylor & Francis, 2026.

    DOI: 10.1080/02331934.2026.2692689
    online unter: https://www.tandfonline.com/doi/citedby/10.1080/02331934.2026.2692689

  7. 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