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Publikationen des Jahres 2023

Zeitschriftenartikel (25)

  1. F. Altenkrüger, A. Denker, P. Hagemann, P. Maaß, G. Steidl.
    PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization.
    Inverse Problems, 39(6), 2023.

    online unter: https://iopscience.iop.org/article/10.1088/1361-6420/acce5e/meta

  2. J. Antorán, R. Barbano, J. Leuschner, J. M. Hernández-Lobato, B. Jin.
    Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior.
    Transactions on Machine Learning Research, 12, 2023.

    online unter: https://openreview.net/forum?id=FWyabz82fH

  3. 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.
    Inverse Problems, 39(12), IOPscience, 2023.

    DOI: 10.1088/1361-6420/ad0660
    online unter: https://iopscience.iop.org/article/10.1088/1361-6420/ad0660

  4. C. Arndt, A. Denker, S. Dittmer, J. Leuschner, J. Nickel, M. Schmidt.
    Model-based deep learning approaches to the Helsinki Tomography Challenge 2022.
    Applied Mathematics for Modern Challenges, 1(2), 2023.

    DOI: 10.3934/ammc.2023007

  5. S. Banert, P. Giselsson, H. Sadeghi.
    Incorporating history and deviations in forward–backward splitting.
    Numerical Algorithms, , 2023.

    DOI: 10.1007/s11075-023-01686-8

  6. S. Banert, P. Giselsson, M. Morin.
    Nonlinear Forward-Backward Splitting with Momentum Correction.
    Set-Valued and Variational Analysis, 31(37), 2023.

    DOI: 10.1007/s11228-023-00700-4

  7. S. Banert, O. Öktem, J. Adler, J. Rudzusika.
    Accelerated Forward-Backward Optimization using Deep Learning.
    Erscheint in SIAM Journal on Optimization

    online unter: https://arxiv.org/abs/2105.05210

  8. N. K. Bellam Muralidhar, C. Gräßle, N. Rauter, A. Mikhaylenko, R. Lammering, D. Lorenz.
    Damage identification in fiber metal laminates using bayesian analysis with model order reduction.
    Computer Methods in Applied Mechanics and Engineering, Part B 403, 2023.

    DOI: 10.1016/j.cma.2022.115737
    online unter: https://arxiv.org/abs/2206.04329

  9. A. Denker, I. Singh, R. Barbano, Z. Kereta, B. Jin, K. Thielemans, P. Maaß, S. Arridge.
    Score-Based Generative Models for PET Image Reconstruction.
    Erscheint in Machine Learning for Biomedical Imaging

    online unter: https://arxiv.org/abs/2308.14190

  10. 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

  11. S. Dittmer, M. Roberts, J. Gilbey, A. Biguri, .. AIX-COVNET Collaboration, J. Preller, J. H. F. Rudd, J. A. D. Aston, C. Schönlieb.
    Navigating the development challenges in creating complex data systems.
    nature machine intelligence, 5:681-686, Springer Verlag, 2023.

    DOI: 10.1038/s42256-023-00665-x
    online unter: https://www.nature.com/articles/s42256-023-00665-x#citeas

  12. A. Ebner, J. Frikel, D. Lorenz, J. Schwab, M. Haltmeier.
    Regularization of inverse problems by filtered diagonal frame decomposition.
    Applied and Computational Harmonic Analysis, 62:66-83, 2023.

    DOI: 10.1016/j.acha.2022.08.005
    online unter: https://arxiv.org/abs/2008.06219

  13. 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

  14. M. Flatken, A. Podobas, R. Fellegara, A. Basermann, J. Holke, D. Knapp, M. Nolde, C. Krullikowski, N. Brown, R. Nash, E. Belikov, S. W. D. Chien, S. Markidis, J. Tierny, J. Vidal, C. Gueunet, J. Guenther, P. Poletti, G. Guzzetta, M. Manica, A. . Zardini, J. Chaboureau, M. Mendes, A. Cardil, S. Monedero, J. Ramirez, A. Gerndt.
    VESTEC: Visual Exploration and Sampling Toolkit for Extreme Computing. Urgent decision making meets HPC: Experiences and Future Challenges.
    IEEE Access Journal, Vol. 11, pp. 87805-87834 , 2023.

    online unter: https://elib.dlr.de/200273/

  15. 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

  16. 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

  17. M. Höffmann, S. Patel, C. Büskens.
    Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints.
    MDPI Open Access Journals Agriculture, 13(11), 2023.

    DOI: 10.3390/agriculture13112112

  18. D. Lorenz, F. Schneppe.
    Chambolle-Pock’s primal-dual method with mismatched adjoint.
    Applied Mathematics & Optimization, 87(22), 2023.

    DOI: 10.1007/s00245-022-09933-5
    online unter: https://arxiv.org/abs/2201.04928

  19. D. Lorenz, F. Schneppe, L. Tondji.
    Linearly convergent adjoint free solution of least squares problems by random descent.
    Inverse Problems, 39(12), 125019, 2023.

    DOI: 10.1088/1361-6420/ad08ed
    online unter: https://arxiv.org/abs/2306.01946

  20. 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

  21. 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

  22. 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

  23. T. Shadbahr, M. Roberts, J. Stanczuk, J. Gilbey, P. Teare, S. Dittmer, M. Thorpe, R. V. Torne, E. Sala, P. Lio, M. Patel, .. AIX-COVNET Collaboration, J. H. F. Rudd, T. Mirtti, A. Rannikko, J. A. D. Aston, J. Tang, C. Schönlieb.
    The impact of imputation quality on machine learning classifiers for datasets with missing values.
    Communication medicine, 3, Springer Verlag, 2023.

    DOI: 10.1038/s43856-023-00356-z
    online unter: https://www.nature.com/articles/s43856-023-00356-z#citeas

  24. M. Wichmann, M. Eden, D. Zvegincev, F. Wiesener, B. Bergmann, A. Schmidt.
    Modeling the wetting behavior of grinding wheels.
    The International Journal of Advanced Manufacturing Technology, 128, 1741–1747, 2023.

    DOI: 10.1007/s00170-023-12002-y

  25. 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 (19)

  1. A. Abels, E. Pitschmann, D. Schmand.
    Prophet Inequalities over Time.
    24th ACM Conference on Economics and Computation (EC 2023), London, Großbritannien.

    DOI: 10.1145/3580507.3597741

  2. P. Chrszon, P. Maurer, G. Saleip, S. Müller, P. M. Fischer, A. Gerndt, M. Felderer.
    Applicability of Model Checking for Verifying Spacecraft Operational Designs.
    26th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS 2023), 01.-06.10.2023, Västerås, Schweden.

    DOI: 10.1109/MODELS58315.2023.00011

  3. R. Fellegara, K. Krösl, S. Markidis, F. Roshani, M. Flatken, J. D. Fritsch, A. Gerndt, A. Fuhrmann, M. Hürbe, D. Stoll, J. Klug, E. V. Ntagiou.
    Explorative, Immersive Visualization of Space Weather Phenomena.
    International Conference on Space Operations, Dubai UAE, 06.-10.03.2023.

    online unter: https://elib.dlr.de/200316/

  4. M. R. Fellows, M. Grobler, N. Megow, A. E. Mouawad, V. Ramamoorthi, F. A. Rosamond, D. Schmand, S. Siebertz.
    On Solution Discovery via Reconfiguration.
    26th European Conference on Artificial Intelligence (ECAI 2023), Krakau, Polen.

    DOI: 10.3233/FAIA230334

  5. M. Flatken, S. Schneegans, R. Fellegara, A. Gerndt.
    Immersive and Interactive 3D Visualization of Large-Scale Geo-Scientific Data.
    IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Shanghai, China, 25.-29.03.2023.

    online unter: https://elib.dlr.de/200276/

  6. 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

  7. 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

  8. P. Kaur Betz, J. Stoll, V. Grappendorf, J. Gilg, M. Klitz, L. Spataro, A. Klein, L. Rothenhäusler, H. Bohnacker, H. Krämer, M. Meyer-Hermann, S. Somogyi, A. Gerndt, M. J. Kühn.
    ESID: Exploring the Design and Development of a Visual Analytics Tool for Epidemiological Emergencies.
    IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes), 22.-27.10.2023, Melbourne, Australien.

    online unter: https://elib.dlr.de/201432/

  9. 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

  10. X. Li, S. Patel, D. Stronzek-Pfeifer, C. Büskens.
    Indoor Localization for an Autonomous Model Car: A Marker-Based Multi-Sensor Fusion Framework.
    2023 IEEE 19th International Conference on Automation Science and Engineering (CASE), 26.-30.08.2023, Auckland, Neuseeland.
    IEEE Xplore: 28. September 2023, 2023.

    DOI: 10.1109/CASE56687.2023.10260399

  11. D. Lüdtke, T. Firchau, C. G. Cortes, A. Lund, A. Nepal, M. Elbarrawy, Z. Hammadeh, J. Meß, P. Kenny, F. Brömer, M. Mirzaagha, G. Saleip, H. Kirstein, C. Kirchhefer, A. Gerndt.
    ScOSA on the Way to Orbit: Reconfigurable High-Performance Computing for Spacecraft.
    IEEE Space Computing Conference (SCC), 18.-21.07.2023, Pasadena, CA, USA.

    online unter: https://elib.dlr.de/196642/

  12. 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

  13. M. Nittscher, M. F. Lameter, R. Barbano, J. Leuschner, B. Jin, P. Maaß.
    SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction.
    Medical Imaging with Deep Learning (MIDL 2023), 10.07.-12.07.2023.

    online unter: https://2023.midl.io/papers/p014

  14. 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

  15. 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

  16. 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

  17. L. Tondji, D. Lorenz, I. Necoara.
    An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization.
    2023 European Control Conference (ECC).

    DOI: 10.23919/ECC57647.2023.10178390

  18. 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, 117:269-274, 2023.
  19. M. Zeumer, J. Gilg, P. Kaur Betz, A. Gerndt.
    VVAFER – Versatile Visual Analytics Framework for Exploration and Research.
    Visualization and Data Analysis Conference, 18.01.2023, San Francisco, CA, IS&T, USA.
    Electronic Imaging, 35:402.1-402.9, 2023.

    online unter: https://elib.dlr.de/193804/

Buchkapitel (3)

  1. G. Albuquerque, P. M. Fischer, A. Syed, A. Bernstein, S. Utzig, A. Gerndt.
    Digital Twins as Foundation for Augmented Reality Applications in Aerospace.
    Springer Handbook of Augmented Reality, A. Yeh Ching Nee, S. Khim Ong (Hrsg.), S. 881-900, Springer Verlag, 2023.

    online unter: https://elib.dlr.de/195233/

  2. S. Bartsch, A. Kolesnikov, C. Büskens, M. Echim.
    Modulare Unterwassermanipulatoren für autonome Unterwassereinsätze.
    KI-Technologie für Unterwasserroboter, F. Kirchner, S. Straube, D. Kühn, N. Hoyer (Hrsg.), S. 103–111, Springer Verlag, 2023.

    DOI: 10.1007/978-3-031-42369-7_8

  3. P. Kampmann, C. Büskens, S. Wang, D. Wübben, A. Dekorsy.
    Adaptive Steuerung für Unterwasser-Greifsysteme.
    KI-Technologie für Unterwasserroboter, F. Kirchner, S. Straube, D. Kühn, N. Hoyer (Hrsg.), S. 127–136, Springer Verlag, 2023.

    DOI: 10.1007/978-3-031-42369-7_10

Qualifikationsarbeiten (5)

  1. A. Folkers.
    Adaptive Bewegungsplanung für taktische Entscheidungen autonomer Fahrzeuge im urbanen Umfeld: Der generische Hybrid A* .
    Dissertationsschrift, Universität Bremen, 2023.

    DOI: 10.26092/elib/2080

  2. P. Gralla.
    Tikhonov Functionals Incorporating Tolerances in Discrepancy Term for Inverse Problems.
    Dissertationsschrift, Universität Bremen, 2023.

    DOI: 10.26092/elib/2097

  3. J. Leuschner.
    Deep Learning for Computed Tomography Reconstruction: Learned Methods, Deep Image Prior, and Uncertaninty Estimation.
    Dissertationsschrift, Universität Bremen, 2023.

    DOI: 10.26092/elib/2704

  4. D. Nganyu Tanyu.
    On the Interplay between Deep Learning Partial Differential Equations and Inverse Problems.
    Dissertationsschrift, Universität Bremen, 2023.
  5. K. Schäfer.
    Decomposition Methods for Parameter Identification and Bilevel Programming.
    Dissertationsschrift, Universität Bremen, 2023.

    DOI: 10.26092/elib/2735

Preprints (18)

  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, 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

  3. R. Barbano, J. Antorán, J. Leuschner, J. M. Hernández-Lobato, B. Jin, Z. Kereta.
    Image Reconstruction via Deep Image Prior Subspaces.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2302.10279

  4. M. Beckmann, A. Bhandari, M. Iske.
    Fourier-Domain Inversion for the Modulo Radon Transform.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2307.13114

  5. M. Beckmann, N. Heilenkötter.
    Equivariant Neural Networks for Indirect Measurements.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2306.16506

  6. 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

  7. A. Constantinescu, P. Lenzner, R. Reiffenhäuser, D. Schmand, G. Varriccio.
    Solving Woeginger's Hiking Problem: Wonderful Partitions in Anonymous Hedonic Games.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2311.02067

  8. 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.
  9. D. Erzmann, S. Dittmer.
    Equivariant Neural Operators for gradient-Consistent Topology Optimization .
    Zur Veröffentlichung eingereicht.
  10. M. Grobler, S. Maaz, N. Megow, A. E. Mouawad, V. Ramamoorthi, D. Schmand, S. Siebertz.
    Solution discovery via reconfiguration for problems in P.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2311.13478

  11. 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

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

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

  13. D. Lorenz, M. Winkler.
    Minimal error momentum Bregman-Kaczmarz.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2307.15435

  14. 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

  15. D. Nganyu Tanyu, J. Ning, A. Hauptmann, B. Jin, P. Maaß.
    Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2310.18636

  16. M. Roberts, A. Hazan, S. Dittmer, J. H. F. Rudd, C. Schönlieb.
    The curious case of the test set AUROC.
    Zur Veröffentlichung eingereicht.
  17. L. Tondji, I. Necoara, D. Lorenz.
    Acceleration and restart for the randomized Bregman-Kaczmarz method.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2310.17338

  18. L. Tondji, I. Tondji, D. Lorenz.
    Adaptive Bregman-Kaczmarz: An approach to solve linear inverse problems with independent noise exactly.
    Zur Veröffentlichung eingereicht.

    online unter: https://arxiv.org/abs/2309.06186