Publikationen des Jahres 2023

Zeitschriftenartikel (8)

1. E. Dierkes, C. Offen, S. Ober-Blöbaum, K. Flaßkamp.
   Hamiltonian neural networks with automatic symmetry detection.
   Chaos: an Interdisciplinary Journal of Nonlinear Science, 33(6), 2023.

   DOI: 10.1063/5.0142969

2. D. Erzmann, S. Dittmer, H. Harms, P. Maaß.
   DL4TO: A Deep Learning Library for Sample-Efficient Topology Optimization.
   Lecture Notes in Computer Science, Geometric Science of Information. GSI 2023 14071, Springer Verlag, 2023.

   DOI: 10.1007/978-3-031-38271-0_54

3. J. Gödeke, G. Rigaud.
   Imaging based on Compton scattering: model uncertainty and data-driven reconstruction methods.
   Inverse Problems, 39(3), 2023.

   DOI: 10.1088/1361-6420/acb2ed

4. D. Hinse, M. Thode, A. Rademacher, K. Pantke, C. Spura.
   Numerical identification of position-dependent friction coefficients from measured displacement data in a bolt-nut connection.
   , Volume 19, September 2023, 101214 , Elsevier, 2023.

   DOI: https://doi.org/10.1016/j.rineng.2023.101214

5. D. Nganyu Tanyu, J. Ning, T. Freudenberg, N. Heilenkötter, A. Rademacher, U. Iben, P. Maaß.
   Deep learning methods for partial differential equations and related parameter identification problems.
   Inverse Problems, 39(10), 2023.

   DOI: 10.1088/1361-6420/ace9d4

6. C. Nikolopoulos, M. Eden, A. Muntean.
   Multiscale simulation of colloids ingressing porous layers with evolving internal structure: A computational study.
   GEM -- International Journal on Geomathematics, 14(1), 19 p., 2023.

   DOI: 10.1007/s13137-022-00211-8

7. R. Ramirez Acosta, C. Wanigasekara, E. Frost, T. Brandt, S. Lehnhoff, C. Büskens.
   Integration of Intelligent Neighbourhood Grids to the German Distribution Grid: A Perspective.
   Energies, 16(11), 2023.

   DOI: 10.3390/en16114319

8. M. Wiesner, C. Büskens.
   Benchmarking solution methods for parameter identification in dynamical systems.
   PAMM, Proceedings in Applied Mathematics and Mechanics, e202300134 , Wiley, 2023.

   online unter: https://doi.org/10.1002/pamm.202300134

Tagungsbeiträge (8)

1. A. Hackenberg, L. Kappertz, S. Rapol, V. Solovievskyi, C. Büskens.
   Optimal photovoltaic plant dimensioning using consumption data.
   GAMM 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics , 15.08-18.08.2022.
   Proceedings in Applied Mathematics & Mechanics, 23(1), Wiley, 2023.

   DOI: 10.1002/pamm.202200250

2. L. Kappertz, C. Büskens.
   Towards modelling of energy storages for use in an intelligent energy management system.
   GAMM 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics , 15.08-18.08.2022.
   Proceedings in Applied Mathematics & Mechanics, 22(1), Wiley, 2023.

   DOI: 10.1002/pamm.202200257

3. D. Klosa, C. Büskens.
   Low Cost Evolutionary Neural Architecture Search (LENAS) Applied to Traffic Forecasting.
   21st IEEE International Conference on Machine Learning and Applications (ICMLA), 12.12.-14.12.2022, Nassau, Bahamas.
   Mach. Learn. Knowl. Extr., 5(3):830-846, 2023.

   DOI: 10.3390/make5030044

4. I. Mykhailiuk, C. Büskens.
   Parametric Stability Score for Local Solutions of Constrained Parametric Nonlinear Programs.
   GAMM 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics , 15.08-18.08.2022.
   Proceedings in Applied Mathematics & Mechanics, 22(1), Wiley, 2023.

   DOI: 10.1002/pamm.202200254

5. R. Simonelli, C. Büskens.
   Modeling and parameter identification for agricultural machines .
   GAMM 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 30.05.-02.06.2023, Dresden, Sachsen.
   Proceedings in Applied Mathematics & Mechanics, Wiley, 2023.

   DOI: 10.1002/pamm.202300204
   online unter: https://onlinelibrary.wiley.com/doi/full/10.1002/pamm.202300204

6. R. Simonelli, M. Höffmann, S. Patel, C. Büskens.
   Optimal Path Tracking: Benchmarking an NMPC for a Wide-Span Autonomous Agricultural Machine.
   European Control Conference (ECC) 2023, Bukarest, Rumänien.
   

   online unter: https://ieeexplore.ieee.org/document/10178268

7. D. Stronzek-Pfeifer, F. M. Chemmadan, S. Patel, C. Büskens.
   LiDAR-based object detection for agricultural robots.
   GAMM 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 30.05.-02.06.2023, Dresden, Sachsen.
   Proceedings in Applied Mathematics & Mechanics, Wiley, 2023.

   online unter: https://doi.org/10.1002/pamm.202300128

8. F. Wiesener, B. Bergmann, M. Wichmann, M. Eden, T. Freudenberg, A. Schmidt.
   Modeling of heat transfer in tool grinding for multiscale simulations.
   CIRP CMMO 2023, 31.05.-02.06.2023, Karlsruhe, Deutschland.
   Procedia CIRP, S. 6 p., 2023.

Preprints (8)

1. H. Albers, T. Kluth.
   Time-dependent parameter identification in a Fokker-Planck equation based magnetization model of large ensembles of nanoparticles.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2307.03560

2. C. Arndt, A. Denker, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, P. Maaß, J. Nickel.
   Invertible residual networks in the context of regularization theory for linear inverse problems.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2306.01335

3. C. Arndt, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, J. Nickel.
   Bayesian view on the training of invertible residual networks for solving linear inverse problems.
   Zur Veröffentlichung eingereicht.

   online unter: https://www.x-mol.net/paper/article/1682514725633245184

4. C. Brandt, T. Kluth, T. Knopp, L. Westen.
   Dynamic image reconstruction with motion priors in application to 3d magnetic particle imaging.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2306.11625

5. S. Dittmer, M. Roberts, J. Preller, .. AIX-COVNET Collaboration, J. H. F. Rudd, J. A. D. Aston, C. Schönlieb.
   Reinterpreting survival analysis in the universal approximator age.
   Zur Veröffentlichung eingereicht.
6. R. Herdt, M. Schmidt, D. Otero Baguer, J. Le Clerc Arrastia, P. Maaß.
   Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2302.02181

7. G. Klaila, A. Stefanou.
   Supervised topological data analysis for MALDI imaging applications.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2302.13948

8. T. Lütjen, F. Schönfeld, J. Leuschner, M. Schmidt, A. Wald, T. Kluth.
   Learning-based approaches for reconstructions with inexact operators in nanoCTapplications.
   Zur Veröffentlichung eingereicht.

   online unter: https://aps.arxiv.org/abs/2307.10474