Publikationen des Jahres 2020

Tagungsbeiträge (13)

1. H. Albers, T. Kluth, T. Knopp.
   MNPDynamics: A computational toolbox for simulating magnetic moment behavior of ensembles of nanoparticles.
   10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
   International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Hrsg.), 6(2):3 pages, Infinite Science Publishing, 2020.

   DOI: 10.18416/IJMPI.2020.2009020

2. N. Bertschinger, M. Hoefer, D. Schmand.
   Strategic Payments in Financial Networks.
   11th Innovations in Theoretical Computer Science Conference (ITCS 2020).
   

   DOI: 10.4230/LIPIcs.ITCS.2020.46

3. 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

4. S. Dittmer, T. Kluth, D. Otero Baguer, B. Maass.
   A Deep Prior Approach to Magnetic Particle Imaging.
   Machine Learning for Medical Image Reconstruction 2020.
   Springer International Publishing, F. Deeba, P. Johnson, T. Würfl, J. C. Ye (Hrsg.), S. 113-122, 2020.

   DOI: 10.1007/978-3-030-61598-7_11

5. L. Evers.
   Benchmarking pre-trained Encoders for real-time Semantic Road Scene Segmentation.
   GAMM 92st Annual Meeting of the international Association of Applied Mathematics and Mechanics, online, 15.03.2021 - 19.03.2021.
   Proceedings in Applied Mathematics & Mechanics, 20(1), WILEY-VCH, 2020.

   DOI: 10.1002/pamm.202000275

6. T. Kluth, P. Szwargulski, T. Knopp.
   Towards accurate modeling of the multidimensional MPI physics.
   10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
   International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Hrsg.), 6(2):2 pages, Infinite Science Publishing, 2020.

   DOI: 10.18416/IJMPI.2020.2009004

7. M. Knauer, C. Büskens.
   The Augmented Reality Sandbox Makes Optimization Visible.
   21th IFAC World Congress, 11.07.-17.07.2020, Berlin, Deutschland.
   Proceedings of the 21th IFAC World Congress, 53(2):17572-17577, 2020.

   DOI: 10.1016/j.ifacol.2020.12.2670

8. M. Lachmann, F. Jung, C. Büskens.
   Computationally efficient identification of databased models applied to a milk cooling system.
   Conference of Computational Interdisciplinary Science, CCIS, 19.03.-22.03.2019, Atlanta, USA.
   Campinas: Galoa, 2020.

   online unter: https://proceedings.science/ccis-2019/papers/computationally-efficient-identification-of-databased-models-applied-to-a-milk-cooling-system

9. M. Möddel, F. Griese, T. Kluth, T. Knopp.
   Estimating orientation using multi-contrast MPI.
   10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
   International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Hrsg.), 6(2):3 pages, Infinite Science Publishing, 2020.

   DOI: 10.18416/IJMPI.2020.2009023

10. I. Mykhailiuk, K. Flaßkamp, C. Büskens, K. Schäfer.
    On the Computation of Convergence Regions for Sequential Nonlinear Programming Problems.
    GAMM 92st Annual Meeting of the international Association of Applied Mathematics and Mechanics, online, 15.03.2021 - 19.03.2021.
    Proceedings in Applied Mathematics & Mechanics, 20(1), WILEY-VCH, 2020.

    DOI: 10.1002/pamm.202000281

11. I. Mykhailiuk, K. Schäfer, K. Flaßkamp, C. Büskens.
    Preferable Minima in Nonlinear Optimization: Definition and Algorithmic Approaches.
    SAM2022, 24.10.-25.10.2022, Montreal, Kanada.
    

    online unter: https://hessenbox.uni-kassel.de/dl/fi226HzF3AJV3g4LFWM4fWE6/daily_program_2020.pdf?inline

12. M. Runge, K. Flaßkamp, C. Büskens.
    Model Predictive Control with Online Nonlinear Parameter Identification for a Robotic System.
    International Conference on Control, Decision and Information Technologies (CoDIT), 29.06.-02.07.2020, Prag, Tschechien.
    Proceedings of CoDIT, 1:312-318, 2020.

    DOI: 10.1109/CoDIT49905.2020.9263886

13. F. Tramer, J. Behrmann, N. Carlini, N. Papernot, J. Jacobsen.
    Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations.
    International Conference on Machine Learning (ICML), 12.07 - 18.07.2020, Wien, Österreich.
    

    online unter: https://arxiv.org/abs/2002.04599