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Publikationen des Jahres 2020

Zeitschriftenartikel (16)

  1. E. Bänsch, A. Luttmann, J. Montalvo Urquizo, A. Schmidt, M. G. Villarreal-Marroquin.
    Simulation and multi-objective optimization to improve the final shape and process efficiency of a laser-based material accumulation process.
    Journal of Mathematics in Industry, 10(2), 30 p., 2020.
  2. M. Beckmann, P. Maaß, J. Nickel.
    Error analysis for filtered back projection reconstructions in Besov spaces.
    Erscheint in Inverse Problems
  3. T. Boskamp, D. Lachmund, R. Casadonte, L. Hauberg-Lotte, J. H. Kobarg, J. Kriegsmann, P. Maaß.
    Using the chemical noise background in MALDI mass spectrometry imaging for mass alignment and calibration.
    Analytical Chemistry, 92(1):1301-1308, 2020.

    DOI: 10.1021/acs.analchem.9b04473
    online unter: https://doi.org/10.1021/acs.analchem.9b04473

  4. S. Dittmer, T. Kluth, P. Maaß, D. Otero Baguer.
    Regularization by architecture: A deep prior approach for inverse problems.
    Journal of Mathematical Imaging and Vision, :456-470, Springer Verlag, 2020.

    DOI: 10.1007/s10851-019-00923-x
    online unter: http://link.springer.com/article/10.1007/s10851-019-00923-x

  5. T. Gerken.
    Dynamic Inverse Wave Problems – Part II: Operator Identification and Applications.
    Inverse Problems, 36(2), IOPscience, 2020.

    DOI: 10.1088/1361-6420/ab47f4
    online unter: https://iopscience.iop.org/article/10.1088/1361-6420/ab47f4

  6. T. Gerken, S. Grützner.
    Dynamic Inverse Wave Problems – Part I: Regularity for the Direct Problem.
    Inverse Problems, 36(2), IOPscience, 2020.

    DOI: 10.1088/1361-6420/ab47ec
    online unter: https://iopscience.iop.org/article/10.1088/1361-6420/ab47ec

  7. H. Haddar, A. Konschin.
    Factorization Method for Imaging a Local Perturbation in Inhomogeneous Periodic Layers from Far Field Measurements.
    Inverse Problems and Imaging, 14(1):133-152, 2020.

    DOI: 10.3934/ipi.2019067
    online unter: https://www.aimsciences.org/article/doi/10.3934/ipi.2019067

  8. M. Jahn, J. Montalvo Urquizo.
    Modeling and simulation of keyhole-based welding as multi-domain problem using the extended finite element method.
    Applied Mathematical Modelling, 82:731-747, Elsevier, 2020.
  9. O. Klein, F. Fogt, S. Hollerbach, G. Nebrich, T. Boskamp, A. Wellmann.
    Classification of Inflammatory Bowel Disease from Formalin‐Fixed, Paraffin‐Embedded Tissue Biopsies via Imaging Mass Spectrometry.
    Proteomics - Clinical Applications, 190131 , Wiley, 2020.

    DOI: 10.1002/prca.201900131

  10. M. Lachmann, J. Maldonado, W. Bergmann, F. Jung, M. Weber, C. Büskens.
    Self-Learning Data-Based Models as Basis of a Universally Applicable Energy Management System.
    Energies 2020, 13(8), 2084, 2020.

    DOI: 10.3390/en13082084

  11. F. Lieb, T. Boskamp, H. Stark.
    Peak detection for MALDI mass spectrometry imaging data using sparse frame multipliers.
    Journal of Proteomics, 103852 225, Elsevier, 2020.

    DOI: 10.1016/j.jprot.2020.103852

  12. T. H. Nguyen, D. Nho Hào, P. Maaß, L. Colombi Ciacchi.
    Mathematical aspects of catalyst positioning in lithium/air batteries.
    Inverse Problems, 36(4), 2020.

    DOI: 10.1088/1361-6420/ab47e6

  13. 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

  14. G. Rigaud, B. Hahn.
    Reconstruction Algorithm For 3D Compton Scattering Imaging With Incomplete Data.
    Erscheint in Inverse Problems in Science and Engineering
  15. L. Siemer, I. Ovsyannikov, J. Rademacher.
    Inhomogeneous domain walls in spintronic nanowires.
    Nonlinearity, 2905 33(6), IOPscience, 2020.

    DOI: 10.1088/1361-6544/ab6f4e

  16. J. von Schroeder, T. Dickhaus.
    Efficient Calculation of the Joint Distribution of Order Statistics.
    Computational Statistics & Data Analysis, 144, Elsevier, 2020.

    online unter: https://doi.org/10.1016/j.csda.2019.106899

Tagungsbeiträge (8)

  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.
    Erscheint in Infinite Science Publishing, T. Knopp, T. M. Buzug (Hrsg.), S. 2 pages.
  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

  3. 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.
    Erscheint in Infinite Science Publishing, T. Knopp, T. M. Buzug (Hrsg.), S. 2 pages.
  4. 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

  5. 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.
    Erscheint in Infinite Science Publishing, T. Knopp, T. M. Buzug (Hrsg.), S. 2 pages.
  6. I. Mykhailiuk, K. Schäfer, K. Flaßkamp, C. Büskens.
    Preferable Minima in Nonlinear Optimization: Definition and Algorithmic Approaches.
    ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 18.07-18.07.2020, Wien, Österreich.

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

  7. 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.
    Erscheint in Proceedings of CoDIT.
  8. 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

Buchkapitel (3)

  1. T. Gerken.
    Dynamic Inverse Problems for the Acoustic Wave Equation.
    Time-dependent Problems in Imaging and Parameter Identification, Time-dependent Problems in Imaging and Parameter Identification, Springer Verlag, 2020.
  2. S. Görres, S. Böttcher, P. Rink, W. Brannath.
    StaVaCare 2.0 - Zusammenhänge zwischen Care-, Case-Mix, Organisation und Qualität in Pflegeheimen.
    Schriftenreihe zur Weiterentwicklung der Pflegeversicherung, GKV Spitzenverband, 2020.
  3. B. Kuhfuß, C. Schattmann, M. Jahn, A. Schmidt, F. Vollertsen, E. Moumi, C. Schenck, M. Herrmann, S. Ishkina, L. Rathmann, L. Heinrich.
    Micro Forming Processes.
    Cold Micro Metal Forming, F. Vollertsen, S. Friedrich, B. Kuhfuß, P. Maaß, C. Thomy, H. Zoch (Hrsg.), Lecture Notes in Production Engineering, S. 27-94, Springer Verlag, 2020.

Qualifikationsarbeiten (2)

  1. C. Etmann.
    Double Backpropagation with Applications to Robustness and Saliency Map Interpretability.
    Dissertationsschrift, Universität Bremen, 2020.
  2. D. Otero Baguer.
    Neural Networks for solving Inverse Problems. Applications in Materials Science and Medical Imaging. (submitted).
    Dissertationsschrift, Universität Bremen, 2020.

Preprints (12)

  1. S. Arridge, P. Fernsel, A. Hauptmann.
    Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2005.14042

  2. J. Behrmann, P. Vicol, K. Wang, R. Grosse, J. Jacobsen.
    Understanding and Mitigating Exploding Inverses in Invertible Neural Networks.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2006.09347

  3. I. Bougoudis, A. Blechschmidt, A. Richter, S. Seo, J. P. Burrows, N. Theys, A. Rinke.
    Long-term Time-series of Arctic Tropospheric BrO derived from UV-VIS Satellite Remote Sensing and its Relation to First Year Sea Ice.
    Zur Veröffentlichung eingereicht.

    DOI: 10.5194/acp-2020-116

  4. S. Dittmer, T. Kluth, D. Otero Baguer, P. Maaß.
    A deep prior approach to magnetic particle imaging.
    Zur Veröffentlichung eingereicht.
  5. S. Dittmer, T. Kluth, M. Henriksen, P. Maaß.
    Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2007.01593

  6. S. Dittmer, C. Schönlieb, P. Maaß.
    Ground Truth Free Denoising by Optimal Transport.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2007.01575

  7. T. Kluth, C. Bathke, M. Jiang, P. Maaß.
    Joint super-resolution image reconstruction and parameter identification in imaging operator: Analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2004.13091

  8. T. Kluth, B. Jin.
    L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2001.06083

  9. L. Kuger, G. Rigaud.
    Joint fan-beam CT and Compton scattering tomography: analysis and image reconstruction.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2008.06699

  10. I. Piotrowska-Kurczewski, G. Sfakianaki.
    Tikhonov functionals with a tolerance measure introduced in the regularization.
    Zur Veröffentlichung eingereicht.

    online unter: http://arxiv.org/abs/2007.06431

  11. M. Steinherr Zazo, J. Rademacher.
    Lyapunov coefficients for Hopf bifurcations in systems with piecewise smooth nonlinearity.
    Zur Veröffentlichung eingereicht.
  12. J. von Schroeder.
    Stable Feature Selection with Applications to MALDI Imaging Mass Spectrometry Data.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2006.15077