Publikationen des Jahres 2019

Tagungsbeiträge (25)

1. J. Behrmann, W. Grathwohl, R. T. Chen, D. Duvenaud, J. Jacobsen.
   Invertible Residual Networks.
   International Conference on Machine Learning (ICML).
   Proceedings of Machine Learning Research, 97:573-582, 2019.

   Long Oral

   online unter: http://proceedings.mlr.press/v97/behrmann19a.html

2. J. Behrmann, P. Vicol, K. Wang, R. Grosse, J. Jacobsen.
   On the Invertibility of Invertible Neural Networks.
   NeurIPS workshop on Machine Learning with Guarantees, 2019.
   

   online unter: https://sites.google.com/view/mlwithguarantees/accepted-papers

3. A. Berger, M. Knauer, C. Büskens.
   Using Parametric Sensitivity Analysis to Determine Pareto Fronts in Multi-Objective Programming.
   30th European Conference On Operational Research (EURO 2019), 23.06.-26.06.2019.
   
4. C. Brauer, D. Lorenz.
   Ergodic bilevel oprimization.
   SPARS 2019.
   
5. C. Brauer, D. Lorenz, A. Tillmann.
   Exact recovery of partially sparse vectors.
   SPARS 2019.
   
6. C. Brauer, Z. Zhao, D. Lorenz, T. Fingscheidt.
   Learning to dequantize speech signals by primal-dual networks: an approach for acoustic sensor networks.
   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
   

   DOI: 10.1109/ICASSP.2019.8683341

7. R. T. Chen, J. Behrmann, D. Duvenaud, J. Jacobsen.
   Residual Flows for Invertible Generative Modeling.
   Advances in Neural Information Processing Systems (NeurIPS).
   32, S. 9916--9926, 2019.

   Spotlight

   online unter: https://papers.nips.cc/paper/9183-residual-flows-for-invertible-generative-modeling

8. T. Czotscher, D. Otero Baguer, F. Vollertsen, I. Piotrowska-Kurczewski, P. Maaß.
   Connection Between Shock Wave Induced Indentations And Hardness By Means Of Neural Networks.
   22nd International Conference on Material Forming (ESAFORM 2019), 08.05.-10.05.2019.
   AIP Conference Proceedings 2113, 100001, Springer Verlag, 2019.

   DOI: 10.1063/1.5112634

9. C. Etmann, S. Lunz, P. Maaß, C. Schönlieb.
   On the Connection Between Adversarial Robustness and Saliency Map Interpretability.
   36th International Conference on Machine Learning, 09.06.-15.06.2019, Los Angeles, USA.
   PMLR 97, 97:1823-1832, 2019.

   online unter: http://proceedings.mlr.press/v97/etmann19a.html

10. A. Folkers, M. Rick, C. Büskens.
    Controlling an Autonomous Vehicle with Deep Reinforcement Learning.
    Intelligent Vehicles Symposium, 09.06.-12.06.2019, Paris, Frankreich.
    Proceedings of the 30th IEEE Intelligent Vehicles Symposium, S. 2025-2031, 2019.

    Best Student Paper

    DOI: 10.1109/ivs.2019.8814124

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

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

12. J. Jacobsen, J. Behrmann, N. Carlini, F. Tramer, N. Papernot.
    Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness.
    SafeML Workshop, ICLR, 2019.
    

    online unter: https://arxiv.org/abs/1903.10484

13. M. Klimm, A. Tönnis, D. Schmand.
    The Online Best Reply Algorithm for Resource Allocation Problems.
    12th International Symposium on Algorithmic Game Theory (SAGT 2019).
    

    DOI: 10.1007/978-3-030-30473-7_14

14. T. Kluth, B. Hahn, C. Brandt.
    Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging.
    International Workshop on Magnetic Particle Imaging 2019.
    International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2019, S. 23-24, Infinite Science Publishing, 2019.
15. M. Kurowski, S. Roy, J. Gehrt, R. Damerius, C. Büskens, D. Abel, T. Jeinsch.
    Multi-Vehicle Guidance, Navigation and Control Towards Autonomous Ship Maneuvering in Confined Waters.
    European Control Conference (ECC) 2019, 25.06.-28.06.2019.
    Supervisory control of multilevel discrete-event systems with a bus structure, S. 2559-2564, 2019.

    DOI: 10.23919/ECC.2019.8795726

16. D. Lorenz, H. Mahler.
    Orlicz-space regularization for optimal transport and algorithms for quadratic regularization.
    NeurIPS Workshop on Optimal Transport and Machine Learning, Vancouver, Kanada.
    

    online unter: https://arxiv.org/abs/1909.06082

17. D. Lorenz, E. Resmerita.
    Flexible sparse regularization with general non-convex penalties.
    SPARS 2019.
    
18. C. Meerpohl, M. Rick, C. Büskens.
    Free-space Polygon Creation based on Occupancy Grid Maps for Trajectory Optimization Methods.
    10th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2019), 03.07.-05.07.2019.
    

    DOI: 10.1016/j.ifacol.2019.08.107

19. C. Niebuhr, A. Schmidt.
    Finite element methods for parabolic problems with time-dependent domains - application to a milling simulation.
    ENUMATH 2017.
    Lecture Notes in Computational Science and Engineering, 126:481-489, Springer Verlag, 2019.
20. M. Rick, J. Clemens, L. Sommer, A. Folkers, K. Schill, C. Büskens.
    Autonomous Driving Based on Nonlinear Model Predictive Control and Multi-Sensor Fusion.
    10th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2019), 03.07.-05.07.2019.
    

    DOI: 10.1016/j.ifacol.2019.08.068

21. K. Schäfer, K. Flaßkamp, J. Fliege, C. Büskens.
    A Combined Homotopy-Optimization Approach to Parameter Identification for Dynamical Systems.
    GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics, 18.02-22.02.2019, Wien, Österreich.
    90, Proc. Appl. Math. Mech., 19, Wiley, 2019.

    DOI: 10.1002/pamm.201900266

22. D. Schmand, M. Schröder, A. Skopalik.
    Network Investment Games with Wardrop Followers.
    46th International Colloquium on Automata, Languages, and Programming (ICALP 2019).
    

    DOI: 10.4230/LIPIcs.ICALP.2019.151

23. S. Schulze, E. King.
    A Frequency‐Uniform and Pitch‐Invariant Time‐Frequency Representation.
    90th GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics (GAMM), 18.02.-22.02.2019, Wien, Österreich.
    Proc. Appl. Math. Mech., 19(1):e201900374, 2019.

    DOI: 10.1002/pamm.201900374

24. M. Westphal, W. Brannath.
    Improving Model Selection by Employing the Test Data.
    36th International Conference on Machine Learning, 09.06.-15.06.2019, Los Angeles, USA.
    PMLR 97, S. 6747-6756, 2019.

    online unter: http://proceedings.mlr.press/v97/westphal19a.html

25. R. Zweigel, J. Gehrt, S. Liu, S. Roy, C. Büskens, M. Kurowski, T. Jeinsch, A. Schubert, M. Gluch, O. Simanski, E. Pairet-Garcia, F. Siemer, D. Abel.
    Optimal Maneuvering and Control of Cooperative Vehicles as Case Study for Maritime Applications within Harbors.
    European Control Conference (ECC) 2019, 25.06.-28.06.2019.
    Supervisory control of multilevel discrete-event systems with a bus structure, S. 3022-3027, 2019.

    DOI: 10.23919/ECC.2019.8796071