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Publikationen des Jahres 2019

Zeitschriftenartikel (31)

  1. A. Ardestani, S. Li, K. Annamalai, B. Lupse, S. Geravandi, A. Dobrowolski, S. Yu, S. Zhu, T. D. Baguley, M. Surakattula, J. Oetjen, L. Hauberg-Lotte, R. Herranz, S. Awal, D. Altenhofen, V. Nguyen-Tran, S. Joseph, P. G. Schultz, A. K. Chatterjee, N. Rogers, M. S. Tremblay, W. Shen, K. Maedler.
    Neratinib protects pancreatic beta cells in diabetes.
    Nature Communications, 10(5015), 2019.

    DOI: 10.1038/s41467-019-12880-5.
    online unter: https://doi.org/10.1038/s41467-019-12880" target="doi">015 | https://doi.org/10.1038/s41467-019-12880

  2. S. Arridge, P. Maaß, O. Öktem, C. Schönlieb.
    Solving inverse problems using data-driven models.
    Acta Numerica, 28:pp. 1-174, Cambridge University Press, 2019.

    DOI: 10.1017/S0962492919000059

  3. F. Bürgel, K. Kazimierski, A. Lechleiter.
    IPscatt—A MATLAB Toolbox for the Inverse Medium Problem in Scattering.
    ACM Transactions on Mathematical Software, 45(4), 45:1–45:20, 2019.

    DOI: 10.1145/3328525

  4. F. Cakoni, H. Haddar, A. Lechleiter.
    On the factorization method for a far field inverse scattering problem in the time domain.
    SIAM Journal on Mathematical Analysis, 51(2):854-872, 2019.

    DOI: 10.1137/18M1214809

  5. K. Chandrasekaran, C. Gottschalk, J. Könemann, B. Peis, D. Schmand, A. Wierz.
    Additive stabilizers for unstable graphs.
    Discrete Optimization, 31:56-78, 2019.

    DOI: 10.1016/j.disopt.2018.08.003

  6. J. Clemens, T. Kluth, T. Reineking.
    β - SLAM: Simultaneous Localization an Grid Mapping with Beta Distributions.
    Information Fusion, 52:62-75, Elsevier, 2019.

    DOI: 10.1016/j.inffus.2018.11.005

  7. K. Demertzis, L. Iliadis, I. Bougoudis.
    Gryphon: a semi-supervised anomaly detection system based on one-class evolving spiking neural network.
    Neural Computing and Applications, , Springer Verlag, 2019.

    DOI: 10.1007/s00521-019-04363-x

  8. P. di Stolfo, A. Rademacher, A. Schröder.
    Dual weighted residual error estimation for the finite cell method.
    Journal of Numerical Mathematics, 27(2):101-122, 2019.
  9. S. Dittmer, E. King, P. Maaß.
    Singular values for ReLU layers.
    IEEE Transactions on Neural Networks and Learning Systems, Article , 2019.

    online unter: https://ieeexplore.ieee.org/document/8891761

  10. I. Dominguez Lacasa, B. Jindra, S. Radosevic, M. Shubbak.
    Paths of technology upgrading in the BRICS economies.
    Research Policy, 48(1):262-280, 2019.

    DOI: 10.1016/j.respol.2018.08.016
    online unter: https://www.sciencedirect.com/science/article/pii/S0048733318302038

  11. M. Eden.
    Homogenization of a Moving Boundary Problem With Prescribed Normal Velocity.
    Advances in Mathematical Sciences and Applications, 28(1):313-341, 2019.
  12. T. Faulwasser, K. Flaßkamp, S. Ober-Blöbaum, K. Worthmann.
    Towards Velocity Turnpikes in Optimal Control of Mechanical Systems.
    IFAC-PapersOnLine, 52(16), 11th IFAC Symposium on Nonlinear Control Systems, Vienna, Austria, 2019.

    DOI: 10.1016/j.ifacol.2019.12.009

  13. K. Flaßkamp, S. Ober-Blöbaum, K. Worthmann.
    Symmetry and Motion Primitives in Model Predictive Control.
    Mathematics of Control, Signals and Systems, :1-31, Springer Verlag, 2019.

    DOI: 10.1007/s00498-019-00246-7

  14. K. Flaßkamp, K. Worthmann, J. Mühlenhoff, C. Greiner-Petter, C. Büskens, J. Oertel, D. Keiner, T. Sattel.
    Towards Optimal Control of Concentric Tube Robots in Stereotactic Neurosurgery.
    Mathematical and Computer Modelling of Dynamical Systems, :560-574, 2019.

    DOI: 10.1080/13873954.2019.1690004

  15. J. Gehrt, R. Zweigel, S. Roy, C. Büskens, M. Kurowski, T. Jeinsch, A. Schubert, M. Gluch, O. Simanski, E. Pairet-Garcia, W. Bruhn, F. Diegel, D. Abel.
    Optimal Maneuvering and Control of Cooperative Vessels within Harbors.
    Journal of Physics, Conference Series, 1357(12019), 2019.

    DOI: 10.1088/1742-6596/1357/1/012019

  16. A. Janz, J. Schramm, M. Echim, F. Schrödel, C. Büskens.
    Model Based Path Optimization for Valet Parking with Trailer.
    IFAC-PapersOnLine, 52(5):85-90, Elsevier, 2019.

    DOI: https://doi.org/10.1016/j.ifacol.2019.09.014

  17. T. Kluth, B. Jin.
    Enhanced Reconstruction in Magnetic Particle Imaging by Whitening and Randomized SVD Approximation.
    Physics in Medicine and Biology, Article ID 125026 64(12), 2019.

    DOI: 10.1088/1361-6560/ab1a4f

  18. T. Kluth, P. Szwargulski, T. Knopp.
    Towards Accurate Modeling of the Multidimensional Magnetic Particle Imaging Physics.
    New Journal of Physics, Article ID 10303 21, 10 pp., 2019.

    online unter: https://iopscience.iop.org/article/10.1088/1367-2630/ab4938/pdf

  19. B. Komander, D. Lorenz, L. Vestweber.
    Denoising of image gradients and to- tal generalized variation denoising.
    Journal of Mathematical Imaging and Vision, 61(1):21-39, 2019.

    DOI: 10.1007/s10851-018-0819-8
    online unter: http://arxiv.org/abs/1712.08585

  20. A. Konschin, A. Lechleiter.
    Reconstruction of a Local Perturbation in Inhomogeneous Periodic Layers from Partial Near Field Measurements.
    Inverse Problems, 35(11), 114006, IOPscience, 2019.

    DOI: 10.1088/1361-6420/ab1c66
    online unter: https://iopscience.iop.org/article/10.1088/1361-6420/ab1c66

  21. S. Kraft, M. Moser, C. Büskens, M. Echim.
    Echtzeitfähige Verbrennungssimulation eines Dual-Fuel-Motors für HiL-Anwendung.
    MTZ - Motortechnische Zeitschrift, 11, Springer Verlag, 2019.

    DOI: 10.1007/s35146-019-0115-1

  22. S. Kraft, M. Moser, C. Büskens, M. Echim.
    Real‑time capable combustion simulation of a dual‑fuel engine for hardware‑in‑the‑loop application.
    Heavy-Duty-, On- und Off-Highway-Motoren, :191-206, Springer Verlag, 2019.

    DOI: 10.1007/978-3-658-25889-4_12

  23. R. Kuhlmann.
    Learning to Steer Nonlinear Interior-Point Methods.
    EURO Journal on Computational Optimization, 7(4):381-419, 2019.

    DOI: 10.1007/s13675-019-00118-4

  24. D. Lorenz, Q. Tran-Dinh.
    Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive stepsizes and convergence.
    Computational Optimization and Applications, 74(1):67-92, 2019.

    DOI: 10.1007/s10589-019-00106-9
    online unter: http://arxiv.org/abs/1801.03765

  25. A. Rademacher.
    Mesh and model adaptivity for frictional contact problems.
    Numerische Mathematik, 142(3):465-523, 2019.
  26. S. Saha, W. Brannath, B. Bornkamp.
    Testing multiple dose combinations in clinical trials.
    Statistical Methods in Medical Research, , 2019.

    DOI: 10.1177/0962280219871969

  27. F. Schöpfer, D. Lorenz.
    Linear convergence of the Randomized Sparse Kaczmarz method.
    Mathematical Programming, 173(1):509-536, 2019.

    DOI: 10.1007/s10107-017-1229-1
    online unter: http://arxiv.org/abs/1610.02889

  28. S. Seo, A. Richter, A. Blechschmidt, I. Bougoudis, J. P. Burrows.
    First high-resolution BrO column retrievals from TROPOMI .
    Atmospheric Measurement Techniques, 12:2913-2932, 2019.

    DOI: 10.5194/amt-12-2913-2019

  29. M. Shubbak.
    Advances in solar photovoltaics: Technology review and patent trends.
    Renewable and Sustainable Energy Reviews, 115, 109383, Elsevier, 2019.

    DOI: 10.1016/j.rser.2019.109383
    online unter: https://www.sciencedirect.com/science/article/pii/S136403211930591X}, author = {Mahmood H. Shubbak

  30. M. Shubbak.
    The technological system of production and innovation: The case of photovoltaic technology.
    Research Policy, 48(4):993-1015, Elsevier, 2019.

    DOI: 10.1016/j.respol.2018.10.003
    online unter: https://www.sciencedirect.com/science/article/pii/S004873331830235X

  31. M. Westphal, W. Brannath.
    Evaluation of Multiple Prediction Models: A Novel View on Model Selection and Performance Assessment.
    Statistical Methods in Medical Research, , 2019.

    DOI: 10.1177/0962280219854487