Publikationen von Maximilian Schmidt

Zeitschriftenartikel (2)

1. D. Otero Baguer, J. Leuschner, M. Schmidt.
   Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods.
   Inverse Problems, 36(9), IOPscience, 2020.

   DOI: https://doi.org/10.1088/1361-6420/aba415

2. J. Leuschner, M. Schmidt, P. Fernsel, D. Lachmund, T. Boskamp, P. Maaß.
   Supervised Non-negative Matrix Factorization Methods for MALDI Imaging Applications.
   Bioinformatics, bty909 , 2018.

   DOI: 10.1093/bioinformatics/bty909

Preprints (2)

1. C. Etmann, M. Schmidt, J. Behrmann, T. Boskamp, L. Hauberg-Lotte, A. Peter, R. Casadonte, J. Kriegsmann, P. Maaß.
   Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/1912.05459

2. J. Leuschner, M. Schmidt, D. Otero Baguer, P. Maaß.
   The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods.
   Zur Veröffentlichung eingereicht.

   online unter: arXiv:1910.01113

Tagungsbeiträge (2)

1. M. Schmidt.
   Around the clock - capsule networks and image transformations.
   PAMM.
   Erscheint in Proceedings in Applied Mathematics and Mechanics.
2. A. Denker, M. Schmidt, J. Leuschner, P. Maaß, J. Behrmann.
   Conditional Normalizing Flows for Low-Dose Computed Tomography Image Reconstruction.
   ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 18.07-18.07.2020, Wien, Österreich.
   

   online unter: https://invertibleworkshop.github.io/accepted_papers/index.html