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 91st 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. A. Folkers, M. Rick, C. Büskens.
   Time-Dependent Hybrid-State A⁎ and Optimal Control for Autonomous Vehicles in Arbitrary and Dynamic Environments.
   21th IFAC World Congress, 11.07.-17.07.2020, Berlin, Deutschland.
   Proceedings of the 21th IFAC World Congress, 53(2):15077-15083, 2020.

   DOI: 10.1016/j.ifacol.2020.12.2029
   online unter: https://www.sciencedirect.com/science/article/pii/S2405896320326653

7. 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

8. 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

9. 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

10. 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

11. I. Mykhailiuk, K. Schäfer, K. Flaßkamp, C. Büskens.
    Preferable Minima in Nonlinear Optimization: Definition and Algorithmic Approaches.
    SPARS 2019.
    

    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