Publications

Articles (9)

  1. 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

  2. P. Fernsel, P. Maaß.
    A Survey on Surrogate Approaches to Non-negative Matrix Factorization.
    Vietnam Journal of Mathematics, 46(4):987-1021, Springer Verlag, 2018.

    DOI: 10.1007/s10013-018-0315-x

  3. J. Behrmann, C. Etmann, T. Boskamp, R. Casadonte, J. Kriegsmann, P. Maaß.
    Deep Learning for Tumor Classification in Imaging Mass Spectrometry.
    Bioinformatics, 34(7):1215-1223, Oxford University Press, 2018.

    DOI: 10.1093/bioinformatics/btx724

  4. T. Kluth.
    Mathematical models for magnetic particle imaging.
    Inverse Problems, Article ID 083001 34(8), 2018.

    DOI: 10.1088/1361-6420/aac535

  5. T. Kluth, B. Jin, G. Li.
    On the Degree of Ill-Posedness of Multi-Dimensional Magnetic Particle Imaging.
    Inverse Problems, Article ID 095006 34(9), 2018.

    DOI: 10.1088/1361-6420/aad015

  6. 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

  7. C. Bathke, T. Kluth, C. Brandt, P. Maaß.
    Improved image reconstruction in magnetic particle imaging using structural a priori information.
    International Journal on Magnetic Particle Imaging, Article ID 1703015, 3(1), 10 pages, 2017.

    DOI: 10.18416/ijmpi.2017.1703015

  8. T. Kluth, P. Maaß.
    Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction.
    International Journal on Magnetic Particle Imaging, Article ID 1707004 3(2), 10 pages, 2017.

    DOI: 10.18416/ijmpi.2017.1707004

  9. T. Gerken, A. Lechleiter.
    Reconstruction of a Time-dependent Potential from Wave Measurements.
    Inverse Problems, Article ID 094001 33(9), IOPscience, 2017.

    Ausgezeichnet als Highlight Paper

    DOI: 10.1088/1361-6420/aa7e07
    online at: http://iopscience.iop.org/article/10.1088/1361-6420/aa7e07

Proceedings (7)

  1. J. Jacobsen, J. Behrmann, R. Zemel, M. Bethge.
    Excessive Invariance Causes Adversarial Vulnerability.
    International Conference on Learning Representations (2019).

    online at: https://openreview.net/forum?id=BkfbpsAcF7

  2. K. Schäfer, K. Flaßkamp, C. Büskens.
    A Numerical Study of the Robustness of Transcription Methods for Parameter Identification Problems.
    89th GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics (GAMM), 19.03.-23.03.2018, München, Deutschland.
    Proc. Appl. Math. Mech., 2018.

    DOI: 10.1002/pamm.201800101

  3. J. Clemens, C. Meerpohl, V. Schwarting, M. Rick, K. Schill, C. Büskens.
    Autonomous In-Ice Exploration of the Saturnian Moon Enceladus.
    69th International Astronautical Congress (IAC), 01.10.-05.10.2018, Bremen, Deutschland.
  4. D. Otero Baguer, I. Piotrowska, P. Maaß.
    Inverse Problems in designing new structural materials.
    7th International Conference on High Performance Scientific Computing, 19.03-23.03.2018, Hanoi, Vietnam.
  5. C. Meerpohl, K. Flaßkamp, C. Büskens.
    Optimization Strategies for Real-Time Control of an Autonomous Melting Probe.
    2018 American Control Conference (ACC), 2018, Milwaukee, WI, USA.

    DOI: 10.23919/ACC.2018.8430877

  6. K. Schäfer, M. Runge, K. Flaßkamp, C. Büskens.
    Parameter Identification for Dynamical Systems Using Optimal Control Techniques.
    European Control Conference (ECC) 2018, 12.06.-15.06.2018, Limassol, Zypern.

    DOI: 10.23919/ECC.2018.8550045

  7. W. Heins, C. Büskens.
    Two-Level Forecast-Based Energy and Load Management for Grid-Connected Local Systems Using General Load and Storage Models.
    18th International Conference on Environment and Electrical Engineering (EEEIC), 12.06-15.06.2018, Palermo, Italien.

Preprints (5)

  1. J. Behrmann, W. Grathwohl, R. T. Chen, D. Duvenaud, J. Jacobsen.
    Invertible Residual Networks.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/1811.00995

  2. A. Konschin, A. Lechleiter.
    Reconstruction of a Local Perturbation in Inhomogeneous Periodic Layers from Partial Near Field Measurements.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/1901.04451

  3. J. Behrmann, S. Dittmer, P. Fernsel, P. Maaß.
    Analysis of Invariance and Robustness via Invertibility of ReLU-Networks.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/1806.09730

  4. S. Dittmer, T. Kluth, P. Maaß, D. Otero Baguer.
    Regularization by architecture: A deep prior approach for inverse problems.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/pdf/1812.03889.pdf

  5. S. Dittmer, E. King, P. Maaß.
    Singular values for ReLU layers.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/1812.02566