Computational Mathematics for Complex Simulation in Science and Engineering

Chair

Mathematical Aspects of Scientific Computing and Computational Science.

Our mission is to bridge the gap between Numerical Mathematics on the one hand, and Computer Science and Applications on the other hand. Only interdisciplinary approaches can provide a reasonable balance of provability, applicabilty and actual implementations, and this predominantly drives our research: We target both applications and foundation research. Current focus areas include, but are not limited to iterative solvers (in particular multigrid and domain decomposition methods), the development of highly efficient parallel mathematical software, inverse problems, and the realisation of numerical techniques for unconventional hardware such as GPUs.

The chair CMCS is part of the Institute for Applied Analysis and Numerical Simulation. In addition, close relations exist to SC SimTech as co-opted fellow, and PI in the Cluster of Excellence 2075. Our research is and has been supported by the German Research Foundation (DFG) within normal project funding, the Priority Programme 1648 (SPP-EXA), as well as by the "Baden-Württemberg Stiftung".

Publikationsliste Mathematik

  1. 2022

    1. E. Agullo et al., “Resiliency in numerical algorithm design for extreme scale simulations,” The International Journal of High Performance ComputingApplications, vol. 36, no. 2, Art. no. 2, 2022, doi: 10.1177/10943420211055188.
    2. C. T. Miller, W. G. Gray, C. E. Kees, I. V. Rybak, and B. J. Shepherd, “Correction to: Modelling Sediment Transport in Three-Phase Surface Water Systems,” J. Hydraul. Res. (submitted), 2022.
    3. S. Burbulla and C. Rohde, “A finite-volume moving-mesh method for two-phase flow in fracturing porous media,” J. Comput. Phys., p. 111031, 2022, doi: https://doi.org/10.1016/j.jcp.2022.111031.
    4. R. Merkle and A. Barth, “Subordinated Gaussian Random Fields in Elliptic Partial Differential Equations,” Stoch PDE: Anal Comp, 2022, [Online]. Available: https://doi.org/10.1007/s40072-022-00246-w
    5. T. Wenzel, G. Santin, and B. Haasdonk, “Stability of convergence rates: Kernel interpolation on non-Lipschitz domains.” arXiv, 2022. doi: 10.48550/ARXIV.2203.12532.
    6. S. Shuva, P. Buchfink, O. Röhrle, and B. Haasdonk, “Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue,” in Large-Scale Scientific Computing, 2022, pp. 402--409.
    7. J. Magiera and C. Rohde, “A molecular–continuum multiscale model for inviscid liquid–vapor flow with sharp interfaces,” J. Comput. Phys., p. 111551, 2022, doi: https://doi.org/10.1016/j.jcp.2022.111551.
    8. F. Massa, L. Ostrowski, F. Bassi, and C. Rohde, “An artificial Equation of State based Riemann solver for a discontinuous Galerkin discretization of the incompressible Navier–Stokes equations,” J. Comput. Phys., p. 110705, 2022, doi: https://doi.org/10.1016/j.jcp.2021.110705.
    9. T. Wenzel, M. Kurz, A. Beck, G. Santin, and B. Haasdonk, “Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows,” in Large-Scale Scientific Computing, Cham, 2022, pp. 410--418.
    10. R. Frank, A. Laptev, and T. Weidl, Schrödinger Operators: Eigenvalues and Lieb–Thirring Inequalities. 2022, p. 512.
    11. V. Zaverkin, D. Holzmüller, R. Schuldt, and J. Kästner, “Predicting properties of periodic systems from cluster data: A case study of liquid water,” The Journal of Chemical Physics, vol. 156, no. 11, Art. no. 11, 2022, doi: 10.1063/5.0078983.
    12. J. Keim, C.-D. Munz, and C. Rohde, “A Relaxation Model for the Non-Isothermal Navier-Stokes-Korteweg Equations in onfined Domains,” arXiv e-prints, 2022. doi: 0.48550/ARXIV.2208.05310.
    13. B. N. Hahn, M.-L. K. Garrido, C. Klingenberg, and S. Warnecke, “Using the Navier-Cauchy equation for motion estimation in dynamic imaging,” Inverse Problems and Imaging, vol. 0, no. 0, Art. no. 0, 2022, doi: 10.3934/ipi.2022018.
    14. F. Mohammadi et al., “A Surrogate-Assisted Uncertainty-Aware Bayesian Validation Framework and its Application to Coupling Free Flow and Porous-Medium Flow,” Comput. Geosci. (submitted), 2022, [Online]. Available: https://arxiv.org/abs/2106.13639
    15. M. Gander, S. Lunowa, and C. Rohde, “Non-overlapping Schwarz Waveform-Relaxation for Nonlinear Advection-Diffusion Equations,” SIAM J. Sci. Comput., 2022, [Online]. Available: http://www.uhasselt.be/Documents/CMAT/Preprints/2021/UP2103.pdf
    16. C. A. Beschle and B. Kovács, “Stability and error estimates for non-linear Cahn–Hilliard-type equations on evolving surfaces,” Numerische Mathematik, pp. 1--48, 2022, doi: 10.1007/s00211-022-01280-5.
    17. M. Zinßer et al., “Irradiation-dependent topology optimization of metallization grid patterns and variation of contact layer thickness used for latitude-based yield gain of thin-film solar modules,” MRS Advances, Aug. 2022, doi: 10.1557/s43580-022-00321-3.
    18. J. Wirth and M. E. Sebih, “On a wave equation with singular dissipation,” Mathematische Nachrichten, vol. 295, no. 8, Art. no. 8, 2022, doi: 10.1002/mana.202000076.
    19. C. T. Miller, W. G. Gray, C. E. Kees, I. Rybak, and B. Shepherd, “Correction to: Modeling Sediment Transport in Three-Phase Surface Water Systems,” J. Hydraul. Res. (submitted), 2022.
    20. R. L. Frank, A. Laptev, and T. Weidl, “An improved one-dimensional Hardy inequality.” 2022. [Online]. Available: https://arxiv.org/abs/2204.00877
    21. D. Seus, F. A. Radu, and C. Rohde, “Towards hybrid two-phase modelling using linear domain decomposition,” Numerical Methods for Partial Differential Equations, vol. n/a, no. n/a, Art. no. n/a, 2022, doi: https://doi.org/10.1002/num.22906.
    22. R. Merkle and A. Barth, “Multilevel Monte Carlo estimators for elliptic PDEs with Lévy-type diffusion coefficient,” BIT Numer Math, 2022, [Online]. Available: https://doi.org/10.1007/s10543-022-00912-4
    23. I. Kröker, S. Oladyshkin, and I. Rybak, “Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems,” Comput. Geosci. (submitted), 2022, doi: 10.21203/rs.3.rs-1742793/v1.
    24. E. Eggenweiler, M. Discacciati, and I. Rybak, “Analysis of the Stokes-Darcy problem with generalised interface conditions,” ESAIM Math. Model. Numer. Anal., vol. 56, pp. 727–742, 2022, doi: 10.1051/m2an/2022025.
    25. P. Gavrilenko et al., “A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows,” in Large-Scale Scientific Computing, Cham, 2022, pp. 378--386.
    26. P. Strohbeck, E. Eggenweiler, and I. Rybak, “A modification of the Beavers-Joseph condition for arbitrary flows to the fluid-porous interface,” Transp. Porous Med. (submitted), 2022, [Online]. Available: https://arxiv.org/abs/2106.15556
    27. S. Burbulla, M. Hörl, and C. Rohde, “Flow in Porous Media with Fractures of Varying Aperture,” arXiv e-prints, 2022. doi: 10.48550/arXiv.2207.09301.
    28. P. Buchfinck, S. Glas, and B. Haasdonk, “Optimal Bases for Symplectic Model Order Reduction of Canonizable Linear Hamiltonian Systems,” 2022.
    29. T. Mel’nyk and C. Rohde, “Asymptotic expansion for convection-dominated transport in a thin graph-like junction,” arXiv e-prints, 2022. doi: 10.48550/ARXIV.2208.05812.
    30. B. Haasdonk, H. Kleikamp, M. Ohlberger, F. Schindler, and T. Wenzel, “A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs.” arXiv, 2022. doi: 10.48550/ARXIV.2204.13454.
    31. R. Merkle and A. Barth, “On some distributional properties of subordinated Gaussian random fields,” Methodol Comput Appl Probab, 2022.
    32. J. Rettberg et al., “Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar.” 2022. doi: https://doi.org/10.48550/arXiv.2203.10061.
    33. S. Burbulla, A. Dedner, M. Hörl, and C. Rohde, “Dune-MMesh: The Dune Grid Module for Moving Interfaces,” J. Open Source Softw., vol. 7, no. 74, Art. no. 74, 2022, doi: 10.21105/joss.03959.
    34. J. Magiera and C. Rohde, “Analysis and Numerics of Sharp and Diffuse Interface Models for Droplet Dynamics,” in Droplet Dynamics under Extreme Ambient Conditions, K. Schulte, C. Tropea, and B. Weigand, Eds. Springer International Publishing, 2022. doi: 10.1007/978-3-031-09008-0_4.
    35. G. Santin, T. Karvonen, and B. Haasdonk, “Sampling based approximation of linear functionals in reproducing kernel Hilbert spaces,” BIT - numerical mathematics, vol. 62, no. 1, Art. no. 1, 2022, doi: 10.1007/s10543-021-00870-3.
  2. 2021

    1. T. Ehring and B. Haasdonk, “Feedback control for a coupled soft tissue system by kernel surrogates,” in Coupled Problems 2021, 2021, no. IS11. doi: 10.23967/coupled.2021.026.
    2. R. D. Benguria et al., Partial differential equations, spectral theory, and mathematical physics—the Ari Laptev anniversary volume. EMS Press, Berlin, 2021. doi: 10.4171/ECR/18.
    3. M. Altenbernd, N.-A. Dreier, C. Engwer, and D. Göddeke, “Towards Local-Failure Local-Recovery in PDE Frameworks: The Case of Linear Solvers,” in High Performance Computing in Science and Engineering -- HPCSE 2019, Jan. 2021, vol. 12456, pp. 17--38. doi: 10.1007/978-3-030-67077-1_2.
    4. T. Holicki and C. W. Scherer, “Algorithm Design and Extremum Control: Convex Synthesis due to Plant Multiplier Commutation,” in Proc. 60th IEEE Conf. Decision and Control, 2021, pp. 3249–3256. doi: 10.1109/CDC45484.2021.9683012.
    5. C. Fiedler, C. W. Scherer, and S. Trimpe, “Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression,” in Proceedings of the AAAI Conference on Artificial Intelligence, 2021, vol. 35, no. 8, pp. 7439–7447. [Online]. Available: https://ojs.aaai.org/index.php/AAAI/article/view/16912
    6. E. Eggenweiler and I. Rybak, “Effective coupling conditions for arbitrary flows in Stokes-Darcy systems,” Multiscale Model. Simul., vol. 19, pp. 731–757, 2021, doi: 10.1137/20M1346638.
    7. A. Rörich, T. A. Werthmann, D. Göddeke, and L. Grasedyck, “Bayesian inversion for electromyography using low-rank tensor formats,” Inverse Problems, vol. 37, no. 5, Art. no. 5, Mar. 2021, doi: 10.1088/1361-6420/abd85a.
    8. R. Cleyton, A. Moroianu, and U. Semmelmann, “Metric connections with parallel skew-symmetric torsion,” Adv. Math., vol. 378, pp. 107519, 50, 2021, doi: 10.1016/j.aim.2020.107519.
    9. R. Lang, “On the eigenvalues of the non-self-adjoint Robin Laplacian on bounded domains and compact quantum graphs.,” Dissertation, Universität Stuttgart, Stuttgart, 2021. doi: 10.18419/opus-11428.
    10. U. Freiberg and S. Kohl, “Box dimension of fractal attractors and their numerical computation,” COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, vol. 95, Apr. 2021, doi: 10.1016/j.cnsns.2020.105615.
    11. P. Buchfink, S. Glas, and B. Haasdonk, “Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds.” 2021. doi: https://doi.org/10.48550/arXiv.2112.10815.
    12. T. Holicki, C. W. Scherer, and S. Trimpe, “Controller Design via Experimental Exploration with Robustness Guarantees,” IEEE Control Syst. Lett., vol. 5, no. 2, Art. no. 2, 2021, doi: 10.1109/LCSYS.2020.3004506.
    13. T. B. Berrett, L. Gyorfi, and H. Walk, “Strongly universally consistent nonparametric regression and    classification with privatised data,” ELECTRONIC JOURNAL OF STATISTICS, vol. 15, no. 1, Art. no. 1, 2021, doi: 10.1214/21-EJS1845.
    14. D. Alonso-Orán, C. Rohde, and H. Tang, “A local-in-time theory for singular SDEs with applications to fluid models with transport noise,” J. Nonlinear Sci., vol. 31, no. 6, Art. no. 6, 2021, doi: doi.org/10.1007/s00332-021-09755-9.
    15. T. Wenzel, G. Santin, and B. Haasdonk, “Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, f P- and f/P-greedy.” arXiv, 2021. doi: 10.48550/ARXIV.2105.07411.
    16. R. Leiteritz, P. Buchfink, B. Haasdonk, and D. Pflüger, “Surrogate-data-enriched Physics-Aware Neural Networks.” 2021.
    17. J. Magiera, “A Molecular--Continuum Multiscale Solver for Liquid--Vapor Flow,” in Small Collaboration: Advanced Numerical Methods for Nonlinear Hyperbolic Balance Laws and Their Applications (hybrid meeting), 2021, vol. 41. doi: 10.14760/OWR-2021-41.
    18. G. Stauch et al., “The Importance of Clinical Data for the Diagnosis of Breast Tumours in North Afghanistan,” Int. Jounal Breast Cancer, vol. Jul 30;2021, p. 6625239, 2021, doi: 10.1155/2021/6625239.
    19. M. Alkämper, J. Magiera, and C. Rohde, “An Interface Preserving Moving Mesh in Multiple SpaceDimensions,” Computing Research Repository, vol. abs/2112.11956, 2021, [Online]. Available: https://arxiv.org/abs/2112.11956
    20. T. Ehring and B. Haasdonk, “Greedy sampling and approximation for realizing feedback control for high dimensional nonlinear systems,” 2021.
    21. L. Brencher and A. Barth, “Scalar conservation laws with stochastic discontinuous flux function,” ArXiv e-prints, arXiv:2107.00549 math.NA, 2021.
    22. M. Geck, “Generalised Gelfand-Graev representations in bad characteristic?,” Transformation Groups, vol. 26, no. 1, Art. no. 1, Mar. 2021, doi: 10.1007/s00031-020-09575-3.
    23. J. Kühnert, D. Göddeke, and M. Herschel, “Provenance-integrated parameter selection and optimization in numerical simulations,” Jul. 2021. [Online]. Available: https://www.usenix.org/conference/tapp2021/presentation/kühnert
    24. A. Beck, J. Dürrwächter, T. Kuhn, F. Meyer, C.-D. Munz, and C. Rohde, “Uncertainty Quantification in High Performance Computational Fluid Dynamics,” in High Performance Computing in Science and Engineering ’19, Cham, 2021, pp. 355--371.
    25. B. Haasdonk, “Model Order Reduction, Applications, MOR Software,” vol. 3, D. Gruyter, Ed. De Gruyter, 2021. doi: 10.1515/9783110499001.
    26. G. Girardi and J. Wirth, “Decay Estimates for a Klein-Gordon Model with Time-Periodic Coeffizients,” in Anomalies in Partial Differential Equations, vol. 43, M. Cicognani, D. del Santo, A. Parmeggiani, and M. Reissig, Eds. Springer, 2021. doi: 10.1007/978-3-030-61346-4_14.
    27. W.-P. Düll, “Validity of the nonlinear Schrödinger approximation for the two-dimensional water wave problem with and without surface tension in the arc length formulation,” Arch. Ration. Mech. Anal., vol. 239, no. 2, Art. no. 2, 2021, doi: 10.1007/s00205-020-01586-4.
    28. S. Schricker, DC. Monje, J. Dippon, M. Kimmel, MD. Alscher, and M. Schanz, “Physician-guided, hybrid genetic testing exerts promising effects on health-related behavior without compromising quality of life,” Sci Rep., vol. 2021 Apr 19;11(1), p. 8494, 2021, doi: 10.1038/s41598-021-87821-8.
    29. B. Haasdonk, B. Hamzi, G. Santin, and D. Wittwar, “Kernel methods for center manifold approximation and a weak              data-based version of the center manifold theorem,” Phys. D, vol. 427, p. Paper No. 133007, 14, 2021, doi: 10.1016/j.physd.2021.133007.
    30. T. Jentsch and G. Weingart, “Jacobi relations on naturally reductive spaces,” ANNALS OF GLOBAL ANALYSIS AND GEOMETRY, vol. 59, no. 1, Art. no. 1, Feb. 2021, doi: 10.1007/s10455-020-09740-7.
    31. T. Hamm and I. Steinwart, “Adaptive Learning Rates for Support Vector Machines Working on Data with Low Intrinsic Dimension,” Ann. Statist., 2021.
    32. P. Buchfink and B. Haasdonk, “Experimental Comparison of Symplectic and Non-symplectic Model Order Reduction an Uncertainty Quantification Problem,” in Numerical Mathematics and Advanced Applications ENUMATH 2019, 2021, vol. 139. doi: 10.1007/978-3-030-55874-1.
    33. J. Dürrwächter, F. Meyer, T. Kuhn, A. Beck, C.-D. Munz, and C. Rohde, “A high-order stochastic Galerkin code for the compressible Euler and Navier-Stokes equations,” Computers & Fluids, vol. 228, pp. 1850044, 20, 2021, doi: 10.1016/j.compfluid.2021.105039.
    34. B. Hilder, “Nonlinear stability of fast invading fronts in a Ginzburg–Landau equation with an additional conservation law,” Nonlinearity, vol. 34, no. 8, Art. no. 8, Jul. 2021, doi: 10.1088/1361-6544/abd612.
    35. L. von Wolff, F. Weinhardt, H. Class, J. Hommel, and C. Rohde, “Investigation of Crystal Growth in Enzymatically Induced Calcite Precipitation by Micro-Fluidic Experimental Methods and Comparison with Mathematical Modeling,” Transp. Porous Media, vol. 137, no. 2, Art. no. 2, 2021, doi: 10.1007/s11242-021-01560-y.
    36. M. Kohr, S. E. Mikhailov, and W. L. Wendland, “Layer potential theory for the anisotropic Stokes system with variable L∞ symmetrically elliptic tensor coefficient,” Math. Methods Appl. Sci., vol. 44, no. 12, Art. no. 12, 2021, doi: 10.1002/mma.7167.
    37. I. Steinwart and S. Fischer, “A Closer Look at Covering Number Bounds for Gaussian Kernels,” J. Complexity, vol. 62, p. 101513, 2021, doi: 10.1016/j.jco.2020.101513.
    38. C. Rohde and L. von Wolff, “A Ternary Cahn-Hilliard-Navier-Stokes model for two phase flow with precipitation and dissolution,” Math. Models Methods Appl. Sci., vol. 31, no. 1, Art. no. 1, 2021, doi: 10.1142/S0218202521500019.
    39. M. Osorno, M. Schirwon, N. Kijanski, R. Sivanesapillai, H. Steeb, and D. Göddeke, “A cross-platform, high-performance SPH toolkit for image-based flow simulations on the pore scale of porous media,” Computer Physics Communications, vol. 267, no. 108059, Art. no. 108059, Oct. 2021, doi: 10.1016/j.cpc.2021.108059.
    40. B. N. Hahn, M. L. Kienle-Garrido, and E. T. Quinto, “Microlocal properties of dynamic Fourier integral operators,” 2021, doi: 10.1007/978-3-030-57784-1_4.
    41. T. Holicki and C. W. Scherer, “Robust Gain-Scheduled Estimation with Dynamic D-Scalings,” IEEE Trans. Autom. Control, 2021, doi: 10.1109/TAC.2021.3052751.
    42. L. Brencher and A. Barth, “Stochastic conservation laws with discontinuous flux functions: The multidimensional case,” 2021.
    43. Y. Miao, C. Rohde, and H. Tang, “Well-posedness for a stochastic Camassa-Holm type equation with higher order nonlinearities.” 2021. [Online]. Available: https://arxiv.org/abs/2105.08607
    44. G. Santin and B. Haasdonk, “Kernel methods for surrogate modeling,” in Model Order Reduction, vol. 1: System-and Data-Driven Methods and Algorithms, P. Benner, W. Schilders, S. Grivet-Talocia, A. Quarteroni, G. Rozza, and L. M. Silveira, Eds. de Gruyter, 2021, pp. 311–354.
    45. J. Magiera, “A Molecular--Continuum Multiscale Solver for Liquid--Vapor Flow: Modeling and Numerical Simulation,” Ph.D. Thesis, 2021. doi: 10.18419/opus-11797.
    46. T. Wenzel, G. Santin, and B. Haasdonk, “Universality and Optimality of Structured Deep Kernel Networks.” arXiv, 2021. doi: 10.48550/ARXIV.2105.07228.
    47. A. Barth and R. Merkle, “Multilevel Monte Carlo estimators for elliptic PDEs with Lévy-type diffusion coefficient,” ArXiv e-prints, arXiv:2108.05604 math.NA, 2021.
    48. A. Wagner et al., “Permeability estimation of regular porous structures: a benchmark for comparison of methods,” Transp. Porous Med., vol. 138, pp. 1–23, 2021, doi: 10.1007/s11242-021-01586-2.
    49. T. Wenzel, G. Santin, and B. Haasdonk, “Analysis of target data-dependent greedy kernel algorithms: Convergence rates for $f$-, $f P$- and $f/P$-greedy.” arXiv, 2021. doi: 10.48550/ARXIV.2105.07411.
    50. D. Wittwar and B. Haasdonk, “Convergence rates for matrix P-greedy variants,” in Numerical mathematics and advanced applications---ENUMATH              2019, vol. 139, Springer, Cham, pp. 1195--1203. doi: 10.1007/978-3-030-55874-1\_119.
    51. M. Kohr, S. E. Mikhailov, and W. L. Wendland, “Dirichlet and transmission problems for anisotropic Stokes and Navier-Stokes systems with L∞ tensor coefficient under relaxed ellipticity condition,” Discrete Contin. Dyn. Syst., vol. 41, no. 9, Art. no. 9, 2021, doi: 10.3934/dcds.2021042.
    52. B. de Rijk and G. Schneider, “Global existence and decay in multi-component reaction-diffusion-advection systems with different velocities: oscillations in time and frequency,” NoDEA, Nonlinear Differ. Equ. Appl., vol. 28, no. 1, Art. no. 1, 2021.
    53. A. Krämer et al., “Multi-physics multi-scale HPC simulations of skeletal muscles,” in High Performance Computing in Science and Engineering ’20: Transactions of the High Performance Computing Center, Stuttgart(HLRS) 2020, W. E. Nagel, D. H. Kröner, and M. M. Resch, Eds. 2021. doi: 10.1007/978-3-030-80602-6_13.
    54. I. Rybak, C. Schwarzmeier, E. Eggenweiler, and U. Rüde, “Validation and calibration of coupled porous-medium and free-flow problems using pore-scale resolved models,” Comput. Geosci., vol. 25, pp. 621–635, 2021, doi: 10.1007/s10596-020-09994-x.
    55. M. Nonnenmacher, D. Reeb, and I. Steinwart, “Which Minimizer Does My Neural Network Converge To?,” in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Cham, 2021, pp. 87--102. doi: https://doi.org/10.1007/978-3-030-86523-8_6.
    56. A. Kollross, “Polar actions on Damek-Ricci spaces,” Differential Geometry and its Applications, vol. 76, p. 101753, Jun. 2021, doi: 10.1016/j.difgeo.2021.101753.
    57. J. Giesselmann, F. Meyer, and C. Rohde, “Error control for statistical solutions of hyperbolic systems of conservation laws,” Calcolo, vol. 58, no. 2, Art. no. 2, 2021, doi: 10.1007/s10092-021-00417-6.
    58. M. Kohr, S. E. Mikhailov, and W. L. Wendland, “Layer potential theory for the anisotropic Stokes system with variable L∞ symmetrically elliptic tensor coeffici,” Math. Methods Appl. Sci., vol. 44, no. 12, Art. no. 12, 2021, doi: 10.1002/mma.7167.
    59. A. Krämer et al., High Performance Computing in Science and Engineering 20. Springer, 2021. doi: 10.1007/978-3-030-80602-6_13.
    60. B. Haasdonk, M. Ohlberger, and F. Schindler, “An adaptive model hierarchy for data-augmented training of kernel models for reactive flow.” arXiv, 2021. doi: 10.48550/ARXIV.2110.12388.
    61. T. Benacchio et al., “Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction,” The International Journal of High Performance Computing Applications, vol. 35, no. 4, Art. no. 4, Feb. 2021, doi: 10.1177/1094342021990433.
    62. H. Hang and I. Steinwart, “Optimal Learning with Anisotropic Gaussian SVMs,” Appl. Comput. Harmon. Anal., no. 55, Art. no. 55, 2021, doi: http://doi.org/10.1016/j.acha.2021.06.004.
    63. F. Echterdiek, D. Kitterer, J. Dippon, G. Paul, V. Schwenger, and J. Latus, “Impact of cardiopulmonary resuscitation on outcome of kidney transplantations from braindead donors aged ≥65 years.,” Clin Transplant., vol. 2021 Aug 13:, p. e14452, 2021, doi: 10.1111/ctr.14452.
    64. B. Haasdonk, T. Wenzel, G. Santin, and S. Schmitt, “Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods,” 2021.
    65. C. Rohde and H. Tang, “On the stochastic Dullin-Gottwald-Holm equation: global existence and wave-breaking phenomena,” NoDEA Nonlinear Differential Equations Appl., vol. 28, no. 1, Art. no. 1, 2021, doi: 10.1007/s00030-020-00661-9.
    66. T. Holicki and C. W. Scherer, “Revisiting and Generalizing the Dual Iteration for Static and Robust Output-Feedback Synthesis,” Int. J. Robust Nonlin., pp. 1–33, 2021, doi: 10.1002/rnc.5547.
    67. T. Wenzel, G. Santin, and B. Haasdonk, “A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution,” 2021.
    68. V. Makogin, M. Oesting, A. Rapp, and E. Spodarev, “Long range dependence for stable random processes,” J. Time Series Anal., vol. 42, no. 2, Art. no. 2, 2021, doi: 10.1111/jtsa.12560.
    69. K. Altmann and F. Witt, “Toric co-Higgs sheaves,” Journal of pure and applied algebra, vol. 225, no. 8, Art. no. 8, 2021, doi: 10.1016/j.jpaa.2020.106634.
    70. C. Rohde and H. Tang, “On a stochastic Camassa-Holm type equation with higher order nonlinearities,” J. Dynam. Differential Equations, vol. 33, pp. 1823–1852, 2021, doi: https://doi.org/10.1007/s10884-020-09872-1.
    71. G. C. Hsiao and W. L. Wendland, Boundary integral equations, vol. 164. Springer, Cham, 2021, p. xx+783. doi: 10.1007/978-3-030-71127-6.
    72. J. Schmalfuss, C. Riethmüller, M. Altenbernd, K. Weishaupt, and D. Göddeke, “Partitioned coupling vs. monolithic block-preconditioning approaches for solving Stokes-Darcy systems,” 2021. doi: 10.23967/coupled.2021.043.
    73. T. Hamm and I. Steinwart, “Intrinsic Dimension Adaptive Partitioning for Kernel Methods,” Fakultät für Mathematik und Physik, Universität Stuttgart, 2021.
    74. B. de Rijk and B. Sandstede, “Diffusive stability against nonlocalized perturbations of              planar wave trains in reaction-diffusion systems,” J. Differential Equations, vol. 274, pp. 1223--1261, 2021, doi: 10.1016/j.jde.2020.10.027.
    75. I. Steinwart and J. F. Ziegel, “Strictly proper kernel scores and characteristic kernels on compact spaces,” Appl. Comput. Harmon. Anal., vol. 51, pp. 510--542, 2021, doi: 10.1016/j.acha.2019.11.005.
    76. J. Veenman, C. W. Scherer, C. Ardura, S. Bennani, V. Preda, and B. Girouart, “IQClab: A new IQC based toolbox for robustness analysis and control design,” in IFAC-PapersOnline, 2021, vol. 54, no. 8, pp. 69--74. doi: 10.1016/j.ifacol.2021.08.583.
    77. B. N. Hahn, “Motion compensation strategies in tomography,” 2021, doi: 10.1007/978-3-030-57784-1_3.
    78. M. Gander, S. Lunowa, and C. Rohde, “Consistent and asymptotic-preserving finite-volume domain decomposition methods for singularly perturbed elliptic equations,” 2021. [Online]. Available: http://www.uhasselt.be/Documents/CMAT/Preprints/2021/UP2103.pdf
    79. K. V. Höllig and J. V. Hörner, Eds., Aufgaben und Lösungen zur Höheren Mathematik 1, 3rd ed. 2021. Springer Berlin Heidelberg, 2021. [Online]. Available: https://doi.org/10.1007/978-3-662-63181-2
  3. 2020

    1. J. B. Kennedy and R. Lang, “On the eigenvalues of quantum graph Laplacians with large complex δ couplings.,” Portugaliae Mathematica. A Journal of the Portuguese Mathematical Society, vol. 77, no. 2, Art. no. 2, 2020.
    2. S. Fischer and I. Steinwart, “Sobolev norm learning rates for regularized least-squares algorithms,” J. Mach. Learn. Res., vol. 21, no. 205, Art. no. 205, Oct. 2020, [Online]. Available: http://jmlr.org/papers/v21/19-734.html
    3. M. Geck, “Green functions and Glauberman degree-divisibility,” Annals of Mathematics, vol. 192, no. 1, Art. no. 1, 2020, doi: 10.4007/annals.2020.192.1.4.
    4. B. de Rijk and G. Schneider, “Global Existence and Decay in Nonlinearly Coupled Reaction-Diffusion-Advection Equations with Different Velocities,” J. Differential Equations, vol. 268, no. 7, Art. no. 7, 2020, doi: 10.1016/j.jde.2019.09.056.
    5. I. Rybak and S. Metzger, “A dimensionally reduced Stokes-Darcy model for fluid flow in fractured porous media,” Appl. Math. Comp., vol. 384, 2020, doi: 10.1016/j.amc.2020.125260.
    6. L. Ostrowski and C. Rohde, “Compressible multicomponent flow in porous media with Maxwell-Stefan diffusion,” Math. Meth. Appl. Sci., vol. 43, no. 7, Art. no. 7, 2020, doi: 10.1002/mma.6185.
    7. N. Ginoux, G. Habib, M. Pilca, and U. Semmelmann, “An Obata-type characterisation of Calabi metrics on line bundles,” North-West. Eur. J. Math., vol. 6, pp. 119--136, i, 2020.
    8. B. Hilder, “Modulating traveling fronts for the Swift-Hohenberg equation in the case of an additional conservation law,” Journal of Differential Equations, vol. 269, no. 5, Art. no. 5, Aug. 2020, doi: 10.1016/j.jde.2020.03.033.
    9. J. Fehr and B. Haasdonk, Eds., IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart,  Germany, May 22-25, 2018: MORCOS 2018. Springer, 2020.
    10. J. Magiera, D. Ray, J. S. Hesthaven, and C. Rohde, “Constraint-aware neural networks for Riemann problems,” J. Comput. Phys., vol. 409, no. 109345, Art. no. 109345, 2020, doi: https://doi.org/10.1016/j.jcp.2020.109345.
    11. I. Steinwart, “Reproducing Kernel Hilbert Spaces Cannot Contain all Continuous Functions on a Compact Metric Space,” Fakultät für Mathematik und Physik, Universität Stuttgart, 2020.
    12. M. Geck, “On Jacob’s construction of the rational canonical form of a matrix,” The Electronic Journal of Linear Algebra, vol. 36, no. 36, Art. no. 36, Apr. 2020, doi: 10.13001/ela.2020.5055.
    13. J. Giesselmann, F. Meyer, and C. Rohde, “A posteriori error analysis for random scalar conservation laws using the Stochastic Galerkin method,” IMA J. Numer. Anal., vol. 40, no. 2, Art. no. 2, 2020, doi: 10.1093/imanum/drz004.
    14. M. Griesemer, M. Hofacker, and U. Linden, “From short-range to contact interactions in the 1d Bose gas,” Math. Phys. Anal. Geom., vol. 23, no. 2, Art. no. 2, 2020, doi: 10.1007/s11040-020-09344-4.
    15. M. Kohr, S. E. Mikhailov, and W. L. Wendland, “Potentials and transmission problems in weighted Sobolev spaces for anisotropic Stokes and Navier–Stokes systems with L∞ strongly elliptic coefficient tensor,” Complex Variables and Elliptic Equations, vol. 65, no. 1, Art. no. 1, 2020, doi: 10.1080/17476933.2019.1631293.
    16. R. Tielen, M. Möller, D. Göddeke, and C. Vuik, “p-multigrid methods and their comparison to h-multigrid methods in Isogeometric Analysis,” Computer Methods in Applied Mechanics and Engineering, vol. 372, p. 113347, Dec. 2020, doi: 10.1016/j.cma.2020.113347.
    17. M. Barreau, C. W. Scherer, F. Gouaisbaut, and A. Seuret, “Integral Quadratic Constraints on Linear Infinite-dimensional Systems for Robust Stability Analysis,” 2020.
    18. A. Barth and R. Merkle, “Subordinated Gaussian Random Fields in Elliptic Partial Differential Equations,” ArXiv e-prints, arXiv:2011.09311 math.NA, 2020.
    19. C. Rohde and L. von Wolff, “Homogenization of non-local Navier-Stokes-Korteweg equations for compressible liquid-vapour flow in porous media,” SIAM J. Math. Anal., vol. 52, no. 6, Art. no. 6, 2020, doi: 10.1137/19M1242434.
    20. A. Vonica et al., “Apcdd1 is a dual BMP/Wnt inhibitor in the developing nervous system and skin,” Developmental Biology, vol. 464, no. 1, Art. no. 1, Aug. 2020, doi: 10.1016/j.ydbio.2020.03.015.
    21. M. L. Barberis, A. Moroianu, and U. Semmelmann, “Generalized vector cross products and Killing forms on negatively curved manifolds,” Geom. Dedicata, vol. 205, pp. 113--127, 2020, doi: 10.1007/s10711-019-00467-9.
    22. P. Buchfink, B. Haasdonk, and S. Rave, “PSD-Greedy Basis Generation for Structure-Preserving Model Order Reduction of Hamiltonian Systems,” in Proceedings of the Conference Algoritmy 2020, Aug. 2020, pp. 151--160. [Online]. Available: http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/1577/829
    23. T. Koch et al., “DuMux 3 – an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling,” Computers & Mathematics with Applications, 2020, doi: https://doi.org/10.1016/j.camwa.2020.02.012.
    24. J. Giesselmann, F. Meyer, and C. Rohde, “An a posteriori error analysis based on non-intrusive spectral projections for systems of random conservation laws,” in Hyperbolic Problems: Theory, Numerics, Applications. Proceedings of the Seventeenth International Conference on Hyperbolic Problems 2018, 2020, vol. 10, pp. 449–456. [Online]. Available: https://www.aimsciences.org/fileAIMS/cms/news/info/upload//c0904f1f-97d5-451f-b068-25f1612b6852.pdf
    25. A. Barth and R. Merkle, “Subordinated Gaussian Random Fields,” ArXiv e-prints, arXiv:2012.06353 math.PR, 2020.
    26. P. Bastian et al., “Exa-Dune - Flexible PDE Solvers, Numerical Methods and Applications,” in Software for Exascale Computing -- SPPEXA 2016--2019, H.-J. Bungartz, S. Reiz, B. Uekermann, P. Neumann, and W. E. Nagel, Eds. Springer, 2020, pp. 225--269. doi: 10.1007/978-3-030-47956-5_9.
    27. J. Giesselmann, F. Meyer, and C. Rohde, “A posteriori error analysis and adaptive non-intrusive numerical schemes for systems of random conservation laws,” BIT Numer. Math., 2020, [Online]. Available: https://doi.org/10.1007/s10543-019-00794-z
    28. M. Geck and G. Malle, “The character theory of finite groups of Lie type. A guided tour,” in Cambridge Studies in Advanced Mathematics, vol. 187, Cambridge University Press, 2020, p. ix+394. doi: https://doi.org/10.1017/9781108779081.
    29. T. Holicki and C. W. Scherer, “Output-Feedback Synthesis for a Class of Aperiodic Impulsive Systems,” in IFAC-PapersOnline, 2020, vol. 53, no. 2, pp. 7299–7304. doi: 10.1016/j.ifacol.2020.12.981.
    30. D. Holzmüller and I. Steinwart, “Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent,” Fakultät für Mathematik und Physik, Universität Stuttgart, 2020.
    31. D. Grunert, J. Fehr, and B. Haasdonk, “Well-scaled, a-posteriori error estimation for model order reduction of large second-order mechanical systems,” ZAMM, vol. 100, no. 8, Art. no. 8, 2020, doi: 10.1002/zamm.201900186.
    32. A. Beck, J. Dürrwächter, T. Kuhn, F. Meyer, C.-D. Munz, and C. Rohde, “$hp$-Multilevel Monte Carlo methods for uncertainty quantification of compressible flows,” SIAM J. Sci. Comput., vol. 42, no. 4, Art. no. 4, 2020, doi: https://doi.org/10.1137/18M1210575.
    33. M. Oesting and A. Schnurr, “Ordinal patterns in clusters of subsequent extremes of regularly varying time series,” Extremes, vol. 23, no. 4, Art. no. 4, 2020, doi: 10.1007/s10687-020-00391-2.
    34. B. Haasdonk, B. Hamzi, G. Santin, and D. Wittwar, “Greedy kernel methods for center manifold approximation,” in Spectral and high order methods for partial differential              equations---ICOSAHOM 2018, vol. 134, Springer, Cham, 2020, pp. 95--106. doi: 10.1007/978-3-030-39647-3\_6.
    35. A. Armiti-Juber and C. Rohde, “On the well-posedness of a nonlinear fourth-order extension of Richards’ equation,” J. Math. Anal. Appl., vol. 487, no. 2, Art. no. 2, 2020, doi: https://doi.org/10.1016/j.jmaa.2020.124005.
    36. M. Geck, “ChevLie: Constructing Lie algebras and Chevalley groups,” Journal of Software for Algebra and Geometry, vol. 10, no. 1, Art. no. 1, May 2020, doi: 10.2140/jsag.2020.10.41.
    37. D. Maier, “BREATHER SOLUTIONS ON DISCRETE NECKLACE GRAPHS,” OPERATORS AND MATRICES, vol. 14, no. 3, Art. no. 3, Sep. 2020, doi: 10.7153/oam-2020-14-48.
    38. L. Brencher and A. Barth, “Hyperbolic Conservation Laws with Stochastic Discontinuous Flux Functions,” in International Conference on Finite Volumes for Complex Applications, 2020, pp. 265--273.
    39. L. Ostrowski, F. C. Massa, and C. Rohde, “A phase field approach to compressible droplet impingement,” in Droplet Interactions and Spray Processes, Cham, 2020, pp. 113–126. [Online]. Available: https://doi.org/10.1007/978-3-030-33338-6_9
    40. C. A. Rösinger and C. W. Scherer, “Lifting to Passivity for $H_2$-Gain-Scheduling Synthesis with Full Block Scalings,” in IFAC-PapersOnline, 2020, vol. 53, no. 2, pp. 7292–7298. doi: 10.1016/j.ifacol.2020.12.570.
    41. S. Michalowsky, C. Scherer, and C. Ebenbauer, “Robust and structure exploiting optimisation algorithms: An integral quadratic constraint approach,” International Journal of Control, vol. 2020, pp. 1–24, 2020, doi: 10.1080/00207179.2020.1745286.
    42. S. Baumstark, G. Schneider, K. Schratz, and D. Zimmermann, “Effective slow dynamics models for a class of dispersive systems,” J. Dyn. Differ. Equations, vol. 32, no. 4, Art. no. 4, 2020.
    43. V. Georgiev, T. Ozawa, M. Ruzhansky, and J. Wirth, Eds., Advances in Harmonic Analysis and Partial Differential Equations. Birkhäuser, 2020. doi: 10.1007/978-3-030-58215-9.
    44. D. Holzmüller and I. Steinwart, “Training two-layer ReLU networks with gradient descent is inconsistent,” arXiv:2002.04861, 2020, [Online]. Available: https://arxiv.org/abs/2002.04861
    45. L. Giraud, U. Rüde, and L. Stals, “Resiliency in Numerical Algorithm Design for Extreme Scale Simulations (Dagstuhl Seminar 20101),” Dagstuhl Reports, vol. 10, no. 3, Art. no. 3, 2020, doi: 10.4230/DagRep.10.3.1.
    46. S. Baumstark, G. Schneider, and K. Schratz, “Effective numerical simulation of the Klein-Gordon-Zakharov system in the Zakharov limit,” in Mathematics of wave phenomena. Selected papers based on the presentations at the conference, Karlsruhe, Germany, July 23--27, 2018, Cham: Birkhäuser, 2020, pp. 37--48.
    47. S. Fischer and I. Steinwart, “Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm,” J. Mach. Learn. Res., no. 205, Art. no. 205, 2020.
    48. T. Jentsch and G. Weingart, “RIEMANNIAN AND KAHLERIAN NORMAL COORDINATES,” ASIAN JOURNAL OF MATHEMATICS, vol. 24, no. 3, Art. no. 3, Jun. 2020.
    49. U. Semmelmann, C. Wang, and M. Y.-K. Wang, “On the linear stability of nearly Kähler 6-manifolds,” Ann. Global Anal. Geom., vol. 57, no. 1, Art. no. 1, 2020, doi: 10.1007/s10455-019-09686-5.
    50. A. P. Polyakova, I. E. Svetov, and B. N. Hahn, “The Singular Value Decomposition of the Operators of the Dynamic Ray Transforms Acting on 2D Vector Fields,” in Numerical Computations: Theory and Algorithms, Cham, 2020, pp. 446--453. doi: 10.1007/978-3-030-40616-5_42.
    51. L. A. Minorics, “Spectral asymptotics for Krein-Feller operators with respect to V-variable Cantor measures,” Forum Mathematicum, vol. 32, no. 1, Art. no. 1, Jan. 2020, doi: 10.1515/forum-2018-0188.
    52. S. Burbulla and C. Rohde, “A fully conforming finite volume approach to two-phase flow in fractured porous media,” in Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples, Cham, 2020, pp. 547–555. doi: https://doi.org/10.1007/978-3-030-43651-3_51.
    53. G. Rigaud and B. N. Hahn, “Reconstruction algorithm for 3D Compton scattering imaging with incomplete data,” Inverse Problems in Science and Engineering, vol. 29, no. 7, Art. no. 7, 2020, doi: 10.1080/17415977.2020.1815723.
    54. G. Schneider, “The KdV approximation for a system with unstable resonances,” Math. Methods Appl. Sci., vol. 43, no. 6, Art. no. 6, 2020.
    55. D. E. Pelinovsky and G. Schneider, “The monoatomic FPU system as a limit of a diatomic FPU system,” Appl. Math. Lett., vol. 107, p. 7, 2020.
    56. L. Ostrowski and C. Rohde, “Phase field modelling for compressible droplet impingement,” in Hyperbolic Problems: Theory, Numerics, Applications. Proceedings of the Seventeenth International Conference on Hyperbolic Problems 2018, 2020, vol. 10, pp. 586–593. [Online]. Available: https://www.aimsciences.org/fileAIMS/cms/news/info/upload//c0904f1f-97d5-451f-b068-25f1612b6852.pdf
    57. A. Bitter, “Virtual levels of multi-particle quantum systems and their implications for the Efimov effect,” Dissertation, Universität Stuttgart, Stuttgart, 2020. doi: 10.18419/opus-11315.
    58. E. Eggenweiler and I. Rybak, “Unsuitability of the Beavers-Joseph interface condition for filtration problems,” J. Fluid Mech., vol. 892, p. A10, 2020, doi: http://dx.doi.org/10.1017/jfm.2020.194.
    59. A. Kollross, “Octonions, triality, the exceptional Lie algebra F4 and polar actions on the Cayley hyperbolic plane,” International Journal of Mathematics, vol. 31, no. 07, Art. no. 07, May 2020, doi: 10.1142/s0129167x20500512.
    60. A. Alla, B. Haasdonk, and A. Schmidt, “Feedback control of parametrized PDEs via model order              reduction and dynamic programming principle,” Adv. Comput. Math., vol. 46, no. 1, Art. no. 1, 2020, doi: 10.1007/s10444-020-09744-8.
    61. J. T. Gerstenberger, S. Burbulla, and D. Kröner, “Discontinuous Galerkin method for incompressible two-phase flows,” Submitted to: Springer Proceedings in Mathematics & Statistics, 2020.
    62. T. Haas, B. de Rijk, and G. Schneider, “MODULATION EQUATIONS NEAR THE ECKHAUS BOUNDARY: THE KdV EQUATION,” SIAM JOURNAL ON MATHEMATICAL ANALYSIS, vol. 52, no. 6, Art. no. 6, 2020, doi: 10.1137/19M1266873.
    63. E. Eggenweiler and I. Rybak, “Interface conditions for arbitrary flows in coupled porous-medium and free-flow systems,” in Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples, 2020, vol. 323, pp. 345--353. doi: 10.1007/978-3-030-43651-3_31.
    64. S. Fischer, “Some new bounds on the entropy numbers of diagonal operators,” J. Approx. Theory, vol. 251, p. 105343, Mar. 2020, doi: 10.1016/j.jat.2019.105343.
    65. J. Berberich, A. Koch, C. W. Scherer, and F. Allgöwer, “Robust data-driven state-feedback design,” in 2020 American Control Conference (ACC), Jul. 2020, pp. 1532–1538. doi: 10.23919/acc45564.2020.9147320.
    66. T. Hitz, J. Keim, C.-D. Munz, and C. Rohde, “A parabolic relaxation model for the Navier-Stokes-Korteweg equations,” J. Comput. Phys., vol. 421, p. 109714, 2020, doi: https://doi.org/10.1016/j.jcp.2020.109714.
    67. I. Berre et al., “Verification benchmarks for single-phase flow in three-dimensional fractured porous media.” 2020.
    68. M. Geck, “Computing Green functions in small characteristic,” Journal of Algebra, vol. 561, pp. 163--199, Nov. 2020, doi: 10.1016/j.jalgebra.2019.12.016.
    69. D. Maier, “Construction of breather solutions for nonlinear Klein-Gordon equations    on periodic metric graphs,” JOURNAL OF DIFFERENTIAL EQUATIONS, vol. 268, no. 6, Art. no. 6, Mar. 2020, doi: 10.1016/j.jde.2019.09.035.
    70. S. E. Blanke, B. N. Hahn, and A. Wald, “Inverse problems with inexact forward operator: iterative regularization and application in dynamic imaging,” Inverse Problems, vol. 36, no. 12, Art. no. 12, 2020, doi: 10.1088/1361-6420/abb5e1.
    71. S. Oladyshkin, F. Mohammadi, I. Kroeker, and W. Nowak, “Bayesian(3)Active Learning for the Gaussian Process Emulator Using    Information Theory,” ENTROPY, vol. 22, no. 8, Art. no. 8, Aug. 2020, doi: 10.3390/e22080890.
    72. J. C. Díaz-Ramos, M. Domínguez-Vázquez, and A. Kollross, “On homogeneous manifolds whose isotropy actions are polar,” manuscripta mathematica, vol. 161, no. 1, Art. no. 1, Jan. 2020, doi: 10.1007/s00229-018-1077-1.
    73. M. Brehler, M. Schirwon, P. M. Krummrich, and D. Göddeke, “Simulation of Nonlinear Signal Propagation in Multimode Fibers on Multi-GPU Systems,” Communications in Nonlinear Science and Numerical Simulation, vol. 84, p. 105150, May 2020, doi: 10.1016/j.cnsns.2019.105150.
    74. A. M. Naveira and U. Semmelmann, “Conformal Killing forms on nearly Kähler manifolds,” Differential Geom. Appl., vol. 70, pp. 101628, 9, 2020, doi: 10.1016/j.difgeo.2020.101628.
    75. J. Brinker and J. Wirth, “Gelfand Triples for the Kohn–Nirenberg Quantization on Homogeneous Lie Groups,” in Advances in Harmonic Analysis and Partial Differential Equations., Birkhäuser, 2020, pp. 51–97. doi: 10.1007/978-3-030-58215-9_3.
    76. T. Haas and G. Schneider, “Failure of the N-wave interaction approximation without imposing    periodic boundary conditions,” ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK, vol. 100, no. 6, Art. no. 6, Jun. 2020, doi: 10.1002/zamm.201900230.
  4. 2019

    1. B. Ammann, K. Kröncke, H. Weiss, and F. Witt, “Holonomy rigidity for Ricci-flat metrics,” Math. Z., vol. 291, no. 1–2, Art. no. 1–2, 2019, doi: 10.1007/s00209-018-2084-3.
    2. T. Wenzel, G. Santin, and B. Haasdonk, “A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution.” 2019.
    3. K. Carlberg, L. Brencher, B. Haasdonk, and A. Barth, “Data-driven time parallelism via forecasting,” SIAM Journal on Scientific Computing, vol. 41, no. 3, Art. no. 3, 2019.
    4. M. Chirilus-Bruckner, D. Maier, and G. Schneider, “Diffusive stability for periodic metric graphs,” Math. Nachr., vol. 292, no. 6, Art. no. 6, 2019.
    5. K. Höllig and J. Hörner, Aufgaben und Lösungen zur Höheren Mathematik. - 1., 2. Auflage., vol. 1. Berlin ; Heidelberg: Springer Spektrum, 2019, pp. x, 235 Seiten.
    6. G. Santin, D. Wittwar, and B. Haasdonk, “Sparse approximation of regularized kernel interpolation by greedy algorithms,” 2019.
    7. A. Bhatt, J. Fehr, and B. Haasdonk, “Model order reduction of an elastic body under large rigid motion,” Proceedings of ENUMATH 2017, vol. Lect. Notes Comput. Sci. Eng., no. 126, Art. no. 126, 2019, doi: 10.1007/978-3-319-96415-7\_23.
    8. R. M. Colombo, P. G. LeFloch, C. Rohde, and K. Trivisa, “Nonlinear Hyperbolic Problems: Modeling, Analysis, and Numerics,” Oberwohlfach Rep., no. 16, Art. no. 16, 2019, [Online]. Available: https://www.ems-ph.org/journals/show_issue.php?issn=1660-8933&vol=16&iss=2
    9. D. Wittwar, G. Santin, and B. Haasdonk, “Part II on matrix valued kernels including analysis,” 2019.
    10. I. Steinwart, “A Sober Look at Neural Network Initializations,” Fakultät für Mathematik und Physik, Universität Stuttgart, 2019.
    11. K. Heil and T. Jentsch, “A special class of symmetric Killing 2-tensors,” JOURNAL OF GEOMETRY AND PHYSICS, vol. 138, pp. 103–123, Apr. 2019, doi: 10.1016/j.geomphys.2018.12.009.
    12. A. Bhatt, J. Fehr, D. Grunert, and B. Haasdonk, “A Posteriori Error Estimation in Model Order Reduction of Elastic Multibody Systems with Large Rigid Motion,” in IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, 2019. doi: DOI:10.1007/978-3-030-21013-7_7.
    13. M. Oesting, M. Schlather, and C. Schillings, “Sampling sup-normalized spectral functions for Brown-Resnick processes,” Stat, vol. 8, pp. e228, 11, 2019, doi: 10.1002/sta4.228.
    14. T. Kuhn, J. Dürrwächter, F. Meyer, A. Beck, C. Rohde, and C.-D. Munz, “Uncertainty quantification for direct aeroacoustic simulations of cavity flows,” J. Theor. Comput. Acoust., vol. 27, no. 1, Art. no. 1, 2019, doi: https://doi.org/10.1142/S2591728518500445.
    15. C. A. Rösinger and C. W. Scherer, “A Flexible Synthesis Framework of Structured Controllers for Networked Systems,” IEEE Trans. Control Netw. Syst., vol. 7, no. 1, Art. no. 1, 2019, doi: 10.1109/TCNS.2019.2914411.
    16. R. Föll, B. Haasdonk, M. Hanselmann, and H. Ulmer, “Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation.” 2019. [Online]. Available: https://openreview.net/forum?id=BkgosiRcKm
    17. L. A. Bianchi, D. Blömker, and G. Schneider, “Modulation equation and SPDEs on unbounded domains,” Commun. Math. Phys., vol. 371, no. 1, Art. no. 1, 2019.
    18. V. Sharanya, G. P. R. Sekhar, and C. Rohde, “Surfactant-induced migration of a spherical droplet in non-isothermal Stokes flow,” Physics of Fluids, vol. 31, no. 1, Art. no. 1, 2019, doi: 10.1063/1.5064694.
    19. G. Baggio, S. Zampieri, and C. W. Scherer, “Gramian Optimization with Input-Power Constraints,” in 58th IEEE Conf. Decision and Control, 2019, pp. 5686–5691. doi: 10.1109/CDC40024.2019.9029169.
    20. A. Armiti-Juber and C. Rohde, “On Darcy-and Brinkman-type models for two-phase flow in asymptotically flat domains,” Comput. Geosci., vol. 23, no. 2, Art. no. 2, 2019, doi: https://doi.org/10.1007/s10596-018-9756-2.
    21. T. Brünnette, G. Santin, and B. Haasdonk, “Greedy Kernel Methods for Accelerating Implicit Integrators for Parametric ODEs,” in Numerical Mathematics and Advanced Applications - ENUMATH 2017, Cham, 2019, pp. 889--896.
    22. M. Griesemer and U. Linden, “Spectral theory of the Fermi polaron,” Ann. Henri Poincaré, vol. 20, no. 6, Art. no. 6, 2019, doi: 10.1007/s00023-019-00796-1.
    23. S. Engelke, R. de Fondeville, and M. Oesting, “Extremal behaviour of aggregated data with an application to downscaling,” Biometrika, vol. 106, no. 1, Art. no. 1, 2019, doi: 10.1093/biomet/asy052.
    24. R. Bauer, P. Cummings, and G. Schneider, “A model for the periodic water wave problem and its long wave amplitude equations,” in Nonlinear water waves. An interdisciplinary interface. Based on the workshop held at the Erwin Schrödinger International Institute for Mathematics and Physics, Vienna, Austria, November 27 -- December 7, 2017, Cham: Birkhäuser, 2019, pp. 123--138.
    25. T. Kluth, B. N. Hahn, and C. Brandt, “Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging,” 2019.
    26. U. Semmelmann and G. Weingart, “The standard Laplace operator,” Manuscripta Math., vol. 158, no. 1–2, Art. no. 1–2, 2019, doi: 10.1007/s00229-018-1023-2.
    27. F. G. Zhang R, Dippon J, “Refined risk stratification for thoracoscopic lobectomy or segmentectomy,” Dis., J Thorac, vol. 2019 Jan;11(1), p. :222-230, 2019, doi: 10.21037/jtd.2018.12.44.
    28. R. Bauer, W.-P. Düll, and G. Schneider, “The Korteweg--de Vries, Burgers and Whitham limits for a spatially periodic Boussinesq model,” Proc. Roy. Soc. Edinburgh Sect. A, vol. 149, no. 1, Art. no. 1, 2019, doi: 10.1017/S0308210518000227.
    29. S. Schricker et al., “Strong Associations Between Inflammation, Pruritus and Mental Health in Dialysis Patients,” Acta Derm Venereol., vol. 2019 May 1;99(6), pp. 524–529, 2019, doi: 10.2340/00015555-3128.
    30. A. Schmidt, D. Wittwar, and B. Haasdonk, “Rigorous and effective a-posteriori error bounds for nonlinear problems -- Application to RB methods,” Advances in Computational Mathematics, 2019, doi: 10.1007/s10444-019-09730-9.
    31. G. Santin and B. Haasdonk, “Kernel Methods for Surrogate Modelling,” University of Stuttgart, 2019.
    32. Y. Homma and U. Semmelmann, “The Kernel of the Rarita-Schwinger Operator on Riemannian Spin Manifolds,” Comm. Math. Phys., vol. 370, no. 3, Art. no. 3, 2019, doi: 10.1007/s00220-019-03324-8.
    33. M. Farooq and I. Steinwart, “Learning Rates for Kernel-Based Expectile Regression,” Mach. Learn., vol. 108, pp. 203--227, 2019, doi: 10.1007/s10994-018-5762-9.
    34. A. Armiti-Juber and C. Rohde, “Existence of weak solutions for a nonlocal pseudo-parabolic model for Brinkman two-phase flow in asymptotically flat porous media,” J. Math. Anal. Appl., vol. 477, no. 1, Art. no. 1, 2019, doi: https://doi.org/10.1016/j.jmaa.2019.04.049.
    35. R. Conlon, A. Degeratu, and F. Rochon, “Quasi-asymptotically conical Calabi-Yau manifolds,” Geom. Topol., vol. 23, no. 1, Art. no. 1, 2019, doi: 10.2140/gt.2019.23.29.
    36. B. N. Hahn and M.-L. Kienle Garrido, “An efficient reconstruction approach for a class of dynamic imaging operators,” Inverse Problems, vol. 35, no. 9, Art. no. 9, 2019, doi: 10.1088/1361-6420/ab178b.
    37. L. Ostrowski and F. Massa, “An incompressible-compressible approach for droplet impact,” in Proceedings of the DIPSI Workshop 2019: Droplet ImpactPhenomena & Spray Investigations, Bergamo, Italy, 17th May 2019, 2019, pp. 18–21. doi: 10.6092/DIPSI2019_pp18-21.
    38. M. Schanz et al., “Urinary TIMP-2·IGFBP7-guided randomized controlled intervention trial to prevent acute kidney injury in the emergency department.,” Transplant., vol. 2019 Nov 1;34(11), pp. 1902–1909, 2019, doi: 10.1093/ndt/gfy186.
    39. T. Holicki and C. W. Scherer, “A Homotopy Approach for Robust Output-Feedback Synthesis,” in Proc. 27th. Med. Conf. Control Autom., 2019, pp. 87–93. doi: 10.1109/MED.2019.8798536.
    40. T. Holicki and C. W. Scherer, “Stability analysis and output-feedback synthesis of hybrid systems affected by piecewise constant parameters via dynamic resetting scalings,” Nonlinear Analysis: Hybrid Systems, vol. 34, pp. 179--208, Nov. 2019, doi: 10.1016/j.nahs.2019.06.003.
    41. D. Seus, F. A. Radu, and C. Rohde, “A linear domain decomposition method for two-phase flow in porous media,” Numerical Mathematics and Advanced Applications ENUMATH 2017, pp. 603–614, 2019, doi: https://doi.org/10.1007/978-3-319-96415-7_55.
    42. D. Wittwar and B. Haasdonk, “Greedy Algorithms for Matrix-Valued Kernels,” in Numerical Mathematics and Advanced Applications ENUMATH 2017, Cham, 2019, pp. 113--121.
    43. M. Geck, “Eigenvalues and Polynomial Equations,” The American Mathematical Monthly, vol. 126, no. 10, Art. no. 10, Nov. 2019, doi: 10.1080/00029890.2019.1651168.
    44. M. Kohr and W. L. Wendland, “Boundary value problems for the Brinkman system with L∞ coefficients in Lipschitz domains on compact Riemannian manifolds. A variational approach,” Journal de Mathématiques Pures et Appliquées, no. 131, Art. no. 131, Nov. 2019, doi: https://doi.org/10.1016/j.matpur.2019.04.002.
    45. M. Hansmann, M. Kohler, and H. Walk, “On the strong universal consistency of local averaging regression    estimates (vol 71, pg 1233, 2019),” ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, vol. 71, no. 5, Art. no. 5, Oct. 2019, doi: 10.1007/s10463-018-0687-4.
    46. N. Mücke and I. Steinwart, “Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning,” Fakultät für Mathematik und Physik, Universität Stuttgart, 2019.
    47. R. Zhang, T. Kyriss, J. Dippon, E. Boedeker, and G. Friedel, “Preoperative serum lactate dehydrogenase level as a predictor of major omplications following thoracoscopic lobectomy: a propensity-adjusted analysis.,” European Journal of Cardio-Thoracic Surgery, vol. 56, no. 2, Art. no. 2, 2019, doi: 10.1093/ejcts/ezz027.
    48. P. Buchfink, A. Bhatt, and B. Haasdonk, “Symplectic Model Order Reduction with Non-Orthonormal Bases,” Mathematical and Computational Applications, vol. 24, no. 2, Art. no. 2, 2019, doi: 10.3390/mca24020043.
    49. A. Defant, M. Mastyo, E. A. Sánchez-Pérez, and I. Steinwart, “Translation invariant maps on function spaces over locally compact groups,” J. Math. Anal. Appl., vol. 470, pp. 795--820, 2019, doi: 10.1016/j.jmaa.2018.10.033.
    50. C. T. Miller, W. G. Gray, C. E. Kees, I. V. Rybak, and B. J. Shepherd, “Modeling sediment transport in three-phase surface water systems,” J. Hydraul. Res., vol. 57, 2019, doi: 10.1080/00221686.2019.1581673.
    51. R. Mazzeo, J. Swoboda, H. Weiss, and F. Witt, “Asymptotic geometry of the Hitchin metric,” Commun. Math. Phys., vol. 367, no. 1, Art. no. 1, 2019, doi: 10.1007/s00220-019-03358-y.
    52. M. Kohr, S. E. Mikhailov, and W. L. Wendland, “Newtonian and Single Layer Potentials for the Stokes System with L∞ Coefficients and the Exterior Dirichlet Problem,” in Analysis as a Life: Dedicated to Heinrich Begehr on the Occasion of his 80th Birthday, S. Rogosin and A. O. Celebi, Eds. Cham: Springer International Publishing, 2019, pp. 237--260. doi: 10.1007/978-3-030-02650-9_12.
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    54. I. Steinwart, “Convergence Types and Rates  in Generic Karhunen-Loève Expansions with Applications to Sample Path Properties,” Potential Anal., vol. 51, pp. 361--395, 2019, doi: 10.1007/s11118-018-9715-5.
    55. A. Denzel, B. Haasdonk, and J. Kästner, “Gaussian Process Regression for Minimum Energy Path Optimization and Transition State Search,” J. Phys. Chem. A, vol. 123, no. 44, Art. no. 44, 2019, [Online]. Available: https://doi.org/10.1021/acs.jpca.9b08239
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  5. 2017

    1. H. Minbashian, H. Adibi, and M. Dehghan, “An adaptive wavelet space-time SUPG method for hyperbolic conservation  laws,” Numerical Methods for Partial Differential Equations, vol. 33, no. 6, Art. no. 6, 2017, doi: 10.1002/num.22180.
    2. M. Geck, “Minuscule weights and Chevalley                      groups,” in Finite Simple Groups: Thirty Years of the Atlas and Beyond (Celebrating the Atlases and Honoring John Conway, November 2-5, 2015 at Princeton University), 2017, vol. 694, pp. 159--176. doi: 10.1090/conm/694/13955.
  6. 2012

    1. M. Feistauer and A.-M. Sändig, “Graded mesh refinement and error estimates of higher order for DGFE  solutions of elliptic boundary value problems in polygons,” Numerical Methods for Partial Differential Equations, vol. 28, no. 4, Art. no. 4, 2012, doi: 10.1002/num.20668.
  7. 2011

    1. A. Lalegname and A. Sändig, “Wave-crack interaction in finite elastic bodies,” International Journal of Fracture, vol. 172, no. 2, Art. no. 2, 2011, doi: 10.1007/s10704-011-9650-6.

Teaching

Have a look at our ongoing and past lectures as well as possible thesis topics.

 

This image shows Dominik Göddeke

Dominik Göddeke

Prof. Dr. rer. nat.

Head of Institute and Head of Group

This image shows Britta Lenz

Britta Lenz

 

Secretary's Office

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