Direkt zu:
Einen ersten Eindruck über die vielfältigen Publikationen der Forschenden des Fachbereichs, nicht nur in begutachteten Fachzeitschriften, gibt die folgende Übersicht exemplarisch für den Zeitraum ab 2017. Einen detaillerteren, evtl. vollständigeren und themenspezifischeren Eindruck vermitteln die Seiten der einzelnen Institute, Arbeitsgruppen und koordinierten Forschungsprogramme.
2023
- Burbulla, S., Formaggia, L., Rohde, C., & Scotti, A. (2023). Modeling fracture propagation in poro-elastic media combining phase-field and discrete fracture models. Comput. Methods Appl. Mech. Engrg., 403. https://doi.org/10.1016/j.cma.2022.115699
- Gander, M. J., Lunowa, S. B., & Rohde, C. (2023). Non-Overlapping Schwarz Waveform-Relaxation for Nonlinear Advection-Diffusion Equations. SIAM J. Sci. Comput., 45(1), A49–A73. https://doi.org/10.1137/21M1415005
- Keim, J., Munz, C.-D., & Rohde, C. (2023). A Relaxation Model for the Non-Isothermal Navier-Stokes-Korteweg Equations in Confined Domains. J. Comput. Phys., 474, 111830. https://doi.org/10.1016/j.jcp.2022.111830
- Miao, Y., Rohde, C., & Tang, H. (2023). Well-posedness for a stochastic Camassa-Holm type equation with higher order nonlinearities. accepted by Stoch. Partial Differ. Equ. Anal. Comput. https://arxiv.org/abs/2105.08607
- Seus, D., Radu, F. A., & Rohde, C. (2023). Towards hybrid two-phase modelling using linear domain decomposition. Numer. Methods Partial Differential Equations, 39(1), 622–656. https://doi.org/10.1002/num.22906
- Strohbeck, P., Eggenweiler, E., & Rybak, I. (2023). A modification of the Beavers-Joseph condition for arbitrary flows to the fluid-porous interface. Transp. Porous Med. (accepted). https://arxiv.org/abs/2106.15556
2022
- Agullo, E., Altenbernd, M., Anzt, H., Bautista-Gomez, L., Benacchio, T., Bonaventura, L., Bungartz, H.-J., Chatterjee, S., Ciorba, F. M., DeBardeleben, N., Drzisga, D., Eibl, S., Engelmann, C., Gansterer, W. N., Giraud, L., Göddeke, D., Heisig, M., Jézéquel, F., Kohl, N., … Wohlmuth, B. (2022). Resiliency in numerical algorithm design for extreme scale simulations. The International Journal of High Performance ComputingApplications, 36(2), 10943420211055188. https://doi.org/10.1177/10943420211055188
- Beschle, C. (2022). Uncertainty visualization: Fundamentals and recent developments, code to produce data and visuals used in Section 5. https://doi.org/10.18419/darus-3154
- Beschle, C., & Kovács, B. (2022). Stability and error estimates for non-linear Cahn–Hilliard-type equations on evolving surfaces. Numerische Mathematik, 1--48. https://doi.org/10.1007/s00211-022-01280-5
- Boege, T., Fritze, R., Görgen, C., Hanselman, J., Iglezakis, D., Kastner, L., Koprucki, T., Krause, T., Lehrenfeld, C., Polla, S., Reidelbach, M., Riedel, C., Saak, J., Schembera, B., Tabelow, K., & Weber, M. (2022). Research-Data Management Planning in the German Mathematical Community. arXiv. https://doi.org/10.48550/ARXIV.2211.12071
- Buchfinck, P., Glas, S., & Haasdonk, B. (2022). Optimal Bases for Symplectic Model Order Reduction of Canonizable Linear Hamiltonian Systems.
- Burbulla, S., & Rohde, C. (2022). A finite-volume moving-mesh method for two-phase flow in fracturing porous media. J. Comput. Phys., 111031. https://doi.org/10.1016/j.jcp.2022.111031
- Burbulla, S., Hörl, M., & Rohde, C. (2022). Flow in Porous Media with Fractures of Varying Aperture. In arXiv e-prints. https://doi.org/10.48550/arXiv.2207.09301
- Burbulla, S., Dedner, A., Hörl, M., & Rohde, C. (2022). Dune-MMesh: The Dune Grid Module for Moving Interfaces. J. Open Source Softw., 7(74), 3959. https://doi.org/10.21105/joss.03959
- Eggenweiler, E., Discacciati, M., & Rybak, I. (2022). Analysis of the Stokes-Darcy problem with generalised interface conditions. ESAIM Math. Model. Numer. Anal., 56, 727–742. https://doi.org/10.1051/m2an/2022025
- Eggenweiler, E. (2022). Interface conditions for arbitrary flows in Stokes-Darcy systems : derivation, analysis and validation. Universität Stuttgart. https://doi.org/10.18419/OPUS-12573
- Frank, R., Laptev, A., & Weidl, T. (2022). Schrödinger Operators: Eigenvalues and Lieb–Thirring Inequalities. In Cambridge Studies in Advanced Mathematics (S. 512).
- Frank, R. L., Laptev, A., & Weidl, T. (2022). An improved one-dimensional Hardy inequality. https://arxiv.org/abs/2204.00877
- Gavrilenko, P., Haasdonk, B., Iliev, O., Ohlberger, M., Schindler, F., Toktaliev, P., Wenzel, T., & Youssef, M. (2022). A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows. In I. Lirkov & S. Margenov (Hrsg.), Large-Scale Scientific Computing (S. 378--386). Springer International Publishing.
- Griesemer, M., & Hofacker, M. (2022). From Short-Range to Contact Interactions in Two-dimensional Many-Body Quantum Systems. Annales Henri Poincaré, 23(8), 2769--2818. https://doi.org/10.1007/s00023-021-01149-7
- Griesemer, M. (2022). Ground states of atoms and molecules in non-relativistic QED. In The Physics and Mathematics of Elliott Lieb (S. 437--450). EMS Press. https://doi.org/10.4171/90-1/18
- Haasdonk, B., Kleikamp, H., Ohlberger, M., Schindler, F., & Wenzel, T. (2022). A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs. arXiv. https://doi.org/10.48550/ARXIV.2204.13454
- Hahn, B. N., Garrido, M.-L. K., Klingenberg, C., & Warnecke, S. (2022). Using the Navier-Cauchy equation for motion estimation in dynamic imaging. Inverse Problems and Imaging, 0(0), 0. https://doi.org/10.3934/ipi.2022018
- Horsch, M. T., & Schembera, B. (2022). Documentation of epistemic metadata by a mid-level ontology of cognitive processes. Proc. JOWO 2022.
- Hsiao, G. C., Sánchez-Vizuet, T., & Wendland, W. L. (2022). A Boundary-Field Formulation for Elastodynamic Scattering. Journal of Elasticity. https://doi.org/10.1007/s10659-022-09964-7
- Hägele, D., Schulz, C., Beschle, C., Booth, H., Butt, M., Barth, A., Deussen, O., & Weiskopf, D. (2022). Uncertainty Visualization: Fundamentals and Recent Developments. it - Information Technology, 64(4–5), 121–132. https://doi.org/10.1515/itit-2022-0033
- Jung, K., Schembera, B., & Gärtner, M. (2022). Best of Both Worlds? Mapping Process Metadata in Digital Humanities and Computational Engineering. Metadata and Semantic Research, 199--205. https://doi.org/10.1007/978-3-030-98876-0_17
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2022). Non-homogeneous Dirichlet-transmission problems for the anisotropic Stokes and Navier-Stokes systems in Lipschitz domains with transversal interfaces. Calc. Var. Partial Differential Equations, 61, Paper No. 198 (2022) 47 pp.
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2022). On some mixed-transmission problems for the anisotropic Stokes and Navier-Stokes systems in Lipschitz domains with transversal interfaces. JMAA, 516(1, 126464), 28 pp. https://doi.org/10.1016/j.jmaa.2022.126464
- Kröker, I., Oladyshkin, S., & Rybak, I. (2022). Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems. Comput. Geosci. (submitted). https://doi.org/10.21203/rs.3.rs-1742793/v1
- Magiera, J., & Rohde, C. (2022). A molecular–continuum multiscale model for inviscid liquid–vapor flow with sharp interfaces. J. Comput. Phys., 111551. https://doi.org/10.1016/j.jcp.2022.111551
- Magiera, J., & Rohde, C. (2022). Analysis and Numerics of Sharp and Diffuse Interface Models for Droplet Dynamics. In K. Schulte, C. Tropea, & B. Weigand (Hrsg.), Droplet Dynamics under Extreme Ambient Conditions. Springer International Publishing. https://doi.org/10.1007/978-3-031-09008-0_4
- Massa, F., Ostrowski, L., Bassi, F., & Rohde, C. (2022). An artificial Equation of State based Riemann solver for a discontinuous Galerkin discretization of the incompressible Navier–Stokes equations. J. Comput. Phys., 110705. https://doi.org/10.1016/j.jcp.2021.110705
- Mehl, L., Beschle, C., Barth, A., & Bruhn, A. (2022). Replication Data for: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. https://doi.org/10.18419/darus-2890
- Mel’nyk, T., & Rohde, C. (2022). Asymptotic expansion for convection-dominated transport in a thin graph-like junction. In arXiv e-prints. https://doi.org/10.48550/ARXIV.2208.05812
- Merkle, R., & Barth, A. (2022). Subordinated Gaussian Random Fields in Elliptic Partial Differential Equations. Stoch PDE: Anal Comp. https://doi.org/10.1007/s40072-022-00246-w
- Merkle, R., & Barth, A. (2022). Multilevel Monte Carlo estimators for elliptic PDEs with Lévy-type diffusion coefficient. BIT Numer Math. https://doi.org/10.1007/s10543-022-00912-4
- Merkle, R., & Barth, A. (2022). On some distributional properties of subordinated Gaussian random fields. Methodol Comput Appl Probab.
- Miller, C. T., Gray, W. G., Kees, C. E., Rybak, I., & Shepherd, B. J. (2022). Correction to: Modelling Sediment Transport in Three-Phase Surface Water Systems. J. Hydraul. Res., 0, 1–4. https://doi.org/10.1080/00221686.2022.2107580
- Mohammadi, F., Eggenweiler, E., Flemisch, B., Oladyshkin, S., Rybak, I., Schneider, M., & Weishaupt, K. (2022). A Surrogate-Assisted Uncertainty-Aware Bayesian Validation Framework and its Application to Coupling Free Flow and Porous-Medium Flow. Comput. Geosci. (submitted). https://arxiv.org/abs/2106.13639
- Rettberg, J., Wittwar, D., Buchfink, P., Brauchler, A., Ziegler, P., Fehr, J., & Haasdonk, B. (2022). Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. https://doi.org/10.48550/arXiv.2203.10061
- Santin, G., Karvonen, T., & Haasdonk, B. (2022). Sampling based approximation of linear functionals in reproducing kernel Hilbert spaces. BIT - Numerical Mathematics, 62(1), 279–310. https://doi.org/10.1007/s10543-021-00870-3
- Shuva, S., Buchfink, P., Röhrle, O., & Haasdonk, B. (2022). Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue. In I. Lirkov & S. Margenov (Hrsg.), Large-Scale Scientific Computing (S. 402--409). Springer International Publishing.
- von Wolff, L., & Pop, I. S. (2022). Upscaling of a Cahn–Hilliard Navier–Stokes model with precipitation and dissolution in a thin strip. Journal of Fluid Mechanics, 941, A49--. https://doi.org/DOI: 10.1017/jfm.2022.308
- Wenzel, T., Santin, G., & Haasdonk, B. (2022). Stability of convergence rates: Kernel interpolation on non-Lipschitz domains. arXiv. https://doi.org/10.48550/ARXIV.2203.12532
- Wenzel, T., Santin, G., & Haasdonk, B. (2022). Analysis of Target Data-Dependent Greedy Kernel Algorithms: Convergence Rates for f-, \$\$f \backslashcdot P\$\$- and f/P-Greedy. Constructive Approximation. https://doi.org/10.1007/s00365-022-09592-3
- Wenzel, T., Kurz, M., Beck, A., Santin, G., & Haasdonk, B. (2022). Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. In I. Lirkov & S. Margenov (Hrsg.), Large-Scale Scientific Computing (S. 410--418). Springer International Publishing.
- Wirth, J., & Sebih, M. E. (2022). On a wave equation with singular dissipation. Mathematische Nachrichten, 295(8), Article 8. https://doi.org/10.1002/mana.202000076
- Zaverkin, V., Holzmüller, D., Schuldt, R., & Kästner, J. (2022). Predicting properties of periodic systems from cluster data: A case study of liquid water. The Journal of Chemical Physics, 156(11), 114103. https://doi.org/10.1063/5.0078983
- Zaverkin, V., Holzmüller, D., Steinwart, I., & Kästner, J. (2022). Exploring chemical and conformational spaces by batch mode deep active learning. Digital Discovery, 1, 605–620. https://doi.org/10.1039/D₂DD00034B
- Zinßer, M., Braun, B., Helder, T., Magorian Friedlmeier, T., Pieters, B., Heinlein, A., Denk, M., Göddeke, D., & Powalla, M. (2022). 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. https://doi.org/10.1557/s43580-022-00321-3
2021
- Alkämper, M., Magiera, J., & Rohde, C. (2021). An Interface Preserving Moving Mesh in Multiple SpaceDimensions. Computing Research Repository, abs/2112.11956. https://arxiv.org/abs/2112.11956
- Alonso-Orán, D., Rohde, C., & Tang, H. (2021). A local-in-time theory for singular SDEs with applications to fluid models with transport noise. J. Nonlinear Sci., 31(6), Paper No. 98, 55. https://doi.org/doi.org/10.1007/s00332-021-09755-9
- Altenbernd, M., Dreier, N.-A., Engwer, C., & Göddeke, D. (2021). Towards Local-Failure Local-Recovery in PDE Frameworks: The Case of Linear Solvers. In T. Kozubek, P. Arbenz, J. Jaros, L. Ríha, J. Sístek, & P. Tichý (Hrsg.), High Performance Computing in Science and Engineering -- HPCSE 2019 (Bd. 12456, S. 17--38). Springer. https://doi.org/10.1007/978-3-030-67077-1_2
- Altmann, K., & Witt, F. (2021). Toric co-Higgs sheaves. Journal of Pure and Applied Algebra, 225(8), 106634. https://doi.org/10.1016/j.jpaa.2020.106634
- Barth, A., & Merkle, R. (2021). Multilevel Monte Carlo estimators for elliptic PDEs with Lévy-type diffusion coefficient. ArXiv e-prints, arXiv:2108.05604 math.NA.
- Beck, A., Dürrwächter, J., Kuhn, T., Meyer, F., Munz, C.-D., & Rohde, C. (2021). Uncertainty Quantification in High Performance Computational Fluid Dynamics. In W. E. Nagel, D. H. Kröner, & M. M. Resch (Hrsg.), High Performance Computing in Science and Engineering ’19 (S. 355--371). Springer International Publishing.
- Benacchio, T., Bonaventura, L., Altenbernd, M., Cantwell, C. D., Düben, P. D., Gillard, M., Giraud, L., Göddeke, D., Raffin, E., Teranishi, K., & Wedi, N. (2021). Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. The International Journal of High Performance Computing Applications, 35(4), 285–311. https://doi.org/10.1177/1094342021990433
- Benguria, R. D., Cianchi, A., Maz’ya, V. G., Davies, E. B., Takhtajan, L. A., Tretter, C., Yafaev, D., & und weitere. (2021). Partial differential equations, spectral theory, and mathematical physics—the Ari Laptev anniversary volume. In P. Exner, R. L. Frank, F. Gesztesy, H. Holden, & T. Weidl (Hrsg.), EMS Series of Congress Reports. EMS Press, Berlin. https://doi.org/10.4171/ECR/18
- Berrett, T. B., Gyorfi, L., & Walk, H. (2021). Strongly universally consistent nonparametric regression and classification with privatised data. ELECTRONIC JOURNAL OF STATISTICS, 15(1), 2430–2453. https://doi.org/10.1214/21-EJS1845
- Brencher, L., & Barth, A. (2021). Scalar conservation laws with stochastic discontinuous flux function. ArXiv e-prints, arXiv:2107.00549 math.NA.
- Brencher, L., & Barth, A. (2021). Stochastic conservation laws with discontinuous flux functions: The multidimensional case.
- Buchfink, P., Glas, S., & Haasdonk, B. (2021). Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds. https://doi.org/10.48550/arXiv.2112.10815
- Buchfink, P., & Haasdonk, B. (2021). Experimental Comparison of Symplectic and Non-symplectic Model Order Reduction an Uncertainty Quantification Problem. In F. J. Vermolen & C. Vuik (Hrsg.), Numerical Mathematics and Advanced Applications ENUMATH 2019 (Bd. 139). Springer International Publishing. https://doi.org/10.1007/978-3-030-55874-1
- Cleyton, R., Moroianu, A., & Semmelmann, U. (2021). Metric connections with parallel skew-symmetric torsion. Adv. Math., 378, 107519, 50. https://doi.org/10.1016/j.aim.2020.107519
- de Rijk, B., & Schneider, G. (2021). Global existence and decay in multi-component reaction-diffusion-advection systems with different velocities: oscillations in time and frequency. NoDEA, Nonlinear Differ. Equ. Appl., 28(1), 38.
- de Rijk, B., & Sandstede, B. (2021). Diffusive stability against nonlocalized perturbations of planar wave trains in reaction-diffusion systems. J. Differential Equations, 274, 1223--1261. https://doi.org/10.1016/j.jde.2020.10.027
- Düll, W.-P. (2021). 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., 239(2), 831--914. https://doi.org/10.1007/s00205-020-01586-4
- Dürrwächter, J., Meyer, F., Kuhn, T., Beck, A., Munz, C.-D., & Rohde, C. (2021). A high-order stochastic Galerkin code for the compressible Euler and Navier-Stokes equations. Computers & Fluids, 228, 1850044, 20. https://doi.org/10.1016/j.compfluid.2021.105039
- Echterdiek, F., Kitterer, D., Dippon, J., Paul, G., Schwenger, V., & Latus, J. (2021). Impact of cardiopulmonary resuscitation on outcome of kidney transplantations from braindead donors aged ≥65 years. Clin Transplant., 2021 Aug 13:, e14452. https://doi.org/10.1111/ctr.14452
- Eggenweiler, E., & Rybak, I. (2021). Effective coupling conditions for arbitrary flows in Stokes-Darcy systems. Multiscale Model. Simul., 19, 731–757. https://doi.org/10.1137/20M1346638
- Ehring, T., & Haasdonk, B. (2021). Feedback control for a coupled soft tissue system by kernel surrogates. Coupled Problems 2021, IS11, Article IS11. https://doi.org/10.23967/coupled.2021.026
- Ehring, T., & Haasdonk, B. (2021). Greedy sampling and approximation for realizing feedback control for high dimensional nonlinear systems.
- Fiedler, C., Scherer, C. W., & Trimpe, S. (2021). Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression. Proceedings of the AAAI Conference on Artificial Intelligence, 35(8), 7439–7447. https://ojs.aaai.org/index.php/AAAI/article/view/16912
- Freiberg, U., & Kohl, S. (2021). Box dimension of fractal attractors and their numerical computation. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 95. https://doi.org/10.1016/j.cnsns.2020.105615
- Gander, M., Lunowa, S., & Rohde, C. (2021). Consistent and asymptotic-preserving finite-volume domain decomposition methods for singularly perturbed elliptic equations. Domain Decomposition Methods in Science and Engineering XXVI. http://www.uhasselt.be/Documents/CMAT/Preprints/2021/UP2103.pdf
- Geck, M. (2021). Generalised Gelfand-Graev representations in bad characteristic? Transformation Groups, 26(1), 305--326. https://doi.org/10.1007/s00031-020-09575-3
- Giesselmann, J., Meyer, F., & Rohde, C. (2021). Error control for statistical solutions of hyperbolic systems of conservation laws. Calcolo, 58(2), Paper No. 23, 29. https://doi.org/10.1007/s10092-021-00417-6
- Girardi, G., & Wirth, J. (2021). Decay Estimates for a Klein-Gordon Model with Time-Periodic Coeffizients. In M. Cicognani, D. del Santo, A. Parmeggiani, & M. Reissig (Hrsg.), Anomalies in Partial Differential Equations (Bd. 43). Springer. https://doi.org/10.1007/978-3-030-61346-4_14
- Haasdonk, B., Hamzi, B., Santin, G., & Wittwar, D. (2021). Kernel methods for center manifold approximation and a weak data-based version of the center manifold theorem. Phys. D, 427, Paper No. 133007, 14. https://doi.org/10.1016/j.physd.2021.133007
- Haasdonk, B. (2021). Model Order Reduction, Applications, MOR Software (D. Gruyter, Hrsg.; Bd. 3). De Gruyter. https://doi.org/10.1515/9783110499001
- Haasdonk, B., Ohlberger, M., & Schindler, F. (2021). An adaptive model hierarchy for data-augmented training of kernel models for reactive flow. arXiv. https://doi.org/10.48550/ARXIV.2110.12388
- Haasdonk, B., Wenzel, T., Santin, G., & Schmitt, S. (2021). Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods.
- Hahn, B. N., Kienle-Garrido, M. L., & Quinto, E. T. (2021). Microlocal properties of dynamic Fourier integral operators. https://doi.org/10.1007/978-3-030-57784-1_4
- Hahn, B. N. (2021). Motion compensation strategies in tomography. https://doi.org/10.1007/978-3-030-57784-1_3
- Hamm, T., & Steinwart, I. (2021). Adaptive Learning Rates for Support Vector Machines Working on Data with Low Intrinsic Dimension. Ann. Statist.
- Hamm, T., & Steinwart, I. (2021). Intrinsic Dimension Adaptive Partitioning for Kernel Methods. Fakultät für Mathematik und Physik, Universität Stuttgart.
- Hang, H., & Steinwart, I. (2021). Optimal Learning with Anisotropic Gaussian SVMs. Appl. Comput. Harmon. Anal., 55, 337–367. https://doi.org/10.1016/j.acha.2021.06.004
- Hilder, B. (2021). Nonlinear stability of fast invading fronts in a Ginzburg–Landau equation with an additional conservation law. Nonlinearity, 34(8), 5538--5575. https://doi.org/10.1088/1361-6544/abd612
- Holicki, T., & Scherer, C. W. (2021). Algorithm Design and Extremum Control: Convex Synthesis due to Plant Multiplier Commutation. Proc. 60th IEEE Conf. Decision and Control, 3249–3256. https://doi.org/10.1109/CDC45484.2021.9683012
- Holicki, T., Scherer, C. W., & Trimpe, S. (2021). Controller Design via Experimental Exploration with Robustness Guarantees. IEEE Control Syst. Lett., 5(2), 641–646. https://doi.org/10.1109/LCSYS.2020.3004506
- Holicki, T., & Scherer, C. W. (2021). Robust Gain-Scheduled Estimation with Dynamic D-Scalings. IEEE Trans. Autom. Control. https://doi.org/10.1109/TAC.2021.3052751
- Holicki, T., & Scherer, C. W. (2021). Revisiting and Generalizing the Dual Iteration for Static and Robust Output-Feedback Synthesis. Int. J. Robust Nonlin., 1–33. https://doi.org/10.1002/rnc.5547
- Holzmüller, D., & Pflüger, D. (2021). Fast Sparse Grid Operations Using the Unidirectional Principle: A Generalized and Unified Framework. In H.-J. Bungartz, J. Garcke, & D. Pflüger (Hrsg.), Sparse Grids and Applications - Munich 2018 (S. 69--100). Springer International Publishing.
- Hsiao, G. C., & Wendland, W. L. (2021). On the propagation of acoustic waves in a thermo-electro-magneto-elastic solid. Applicable Analysis, 101 (2022)(0), 3785–3803. https://doi.org/10.1080/00036811.2021.1986027
- Hsiao, G. C., & Wendland, W. L. (2021). Boundary integral equations. In Applied Mathematical Sciences (Bd. 164, S. xx+783). Springer, Cham. https://doi.org/10.1007/978-3-030-71127-6
- Aufgaben und Lösungen zur Höheren Mathematik 1. (2021). In K. V. Höllig & J. V. Hörner (Hrsg.), Springer eBook Collection (3rd ed. 2021.). https://doi.org/10.1007/978-3-662-63181-2
- Jentsch, T., & Weingart, G. (2021). Jacobi relations on naturally reductive spaces. ANNALS OF GLOBAL ANALYSIS AND GEOMETRY, 59(1), 109–156. https://doi.org/10.1007/s10455-020-09740-7
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2021). Layer potential theory for the anisotropic Stokes system with variable L∞ symmetrically elliptic tensor coefficient. Math. Methods Appl. Sci., 44(12), 9641--9674. https://doi.org/10.1002/mma.7167
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2021). Dirichlet and transmission problems for anisotropic Stokes and Navier-Stokes systems with L∞ tensor coefficient under relaxed ellipticity condition. Discrete Contin. Dyn. Syst., 41(9), 4421--4460. https://doi.org/10.3934/dcds.2021042
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2021). Layer potential theory for the anisotropic Stokes system with variable L∞ symmetrically elliptic tensor coeffici. Math. Methods Appl. Sci., 44(12), 9641--9674. https://doi.org/10.1002/mma.7167
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- Ostrowski, L., & Rohde, C. (2020). Phase field modelling for compressible droplet impingement. In A. Bressan, M. Lewicka, D. Wang, & Y. Zheng (Hrsg.), Hyperbolic Problems: Theory, Numerics, Applications. Proceedings of the Seventeenth International Conference on Hyperbolic Problems 2018 (Bd. 10, S. 586–593). AIMS Series on Applied Mathematics. https://www.aimsciences.org/fileAIMS/cms/news/info/upload//c0904f1f-97d5-451f-b068-25f1612b6852.pdf
- Pelinovsky, D. E., & Schneider, G. (2020). The monoatomic FPU system as a limit of a diatomic FPU system. Appl. Math. Lett., 107, 7.
- Polyakova, A. P., Svetov, I. E., & Hahn, B. N. (2020). The Singular Value Decomposition of the Operators of the Dynamic Ray Transforms Acting on 2D Vector Fields. In Y. D. Sergeyev & D. E. Kvasov (Hrsg.), Numerical Computations: Theory and Algorithms (S. 446--453). Springer International Publishing. https://doi.org/10.1007/978-3-030-40616-5_42
- Rigaud, G., & Hahn, B. N. (2020). Reconstruction algorithm for 3D Compton scattering imaging with incomplete data. Inverse Problems in Science and Engineering, 29(7), 967--989. https://doi.org/10.1080/17415977.2020.1815723
- Rohde, C., & von Wolff, L. (2020). Homogenization of non-local Navier-Stokes-Korteweg equations for compressible liquid-vapour flow in porous media. SIAM J. Math. Anal., 52(6), 6155–6179. https://doi.org/10.1137/19M1242434
- Rybak, I., & Metzger, S. (2020). A dimensionally reduced Stokes-Darcy model for fluid flow in fractured porous media. Appl. Math. Comp., 384. https://doi.org/10.1016/j.amc.2020.125260
- Rösinger, C. A., & Scherer, C. W. (2020). Lifting to Passivity for $H_2$-Gain-Scheduling Synthesis with Full Block Scalings. IFAC-PapersOnline, 53(2), 7292–7298. https://doi.org/10.1016/j.ifacol.2020.12.570
- Schneider, G. (2020). The KdV approximation for a system with unstable resonances. Math. Methods Appl. Sci., 43(6), 3185--3199.
- Semmelmann, U., Wang, C., & Wang, M. Y.-K. (2020). On the linear stability of nearly Kähler 6-manifolds. Ann. Global Anal. Geom., 57(1), 15--22. https://doi.org/10.1007/s10455-019-09686-5
- Steinwart, I. (2020). Reproducing Kernel Hilbert Spaces Cannot Contain all Continuous Functions on a Compact Metric Space. Fakultät für Mathematik und Physik, Universität Stuttgart.
- Tielen, R., Möller, M., Göddeke, D., & Vuik, C. (2020). p-multigrid methods and their comparison to h-multigrid methods in Isogeometric Analysis. Computer Methods in Applied Mechanics and Engineering, 372, 113347. https://doi.org/10.1016/j.cma.2020.113347
- Vonica, A., Bhat, N., Phan, K., Guo, J., Iancu, L., Weber, J. A., Karger, A., Cain, J. W., Wang, E. C. E., DeStefano, G. M., O’Donnell-Luria, A. H., Christiano, A. M., Riley, B., Butler, S. J., & Luria, V. (2020). Apcdd1 is a dual BMP/Wnt inhibitor in the developing nervous system and skin. Developmental Biology, 464(1), 71--87. https://doi.org/10.1016/j.ydbio.2020.03.015
2019
- Ammann, B., Kröncke, K., Weiss, H., & Witt, F. (2019). Holonomy rigidity for Ricci-flat metrics. Math. Z., 291(1–2), 303--311. https://doi.org/10.1007/s00209-018-2084-3
- Armiti-Juber, A., & Rohde, C. (2019). On Darcy-and Brinkman-type models for two-phase flow in asymptotically flat domains. Comput. Geosci., 23(2), 285–303. https://doi.org/10.1007/s10596-018-9756-2
- Armiti-Juber, A., & Rohde, C. (2019). Existence of weak solutions for a nonlocal pseudo-parabolic model for Brinkman two-phase flow in asymptotically flat porous media. J. Math. Anal. Appl., 477(1), 592–612. https://doi.org/10.1016/j.jmaa.2019.04.049
- Baggio, G., Zampieri, S., & Scherer, C. W. (2019). Gramian Optimization with Input-Power Constraints. 58th IEEE Conf. Decision and Control, 5686–5691. https://doi.org/10.1109/CDC40024.2019.9029169
- Bauer, R., Cummings, P., & Schneider, G. (2019). 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 (S. 123--138). Cham: Birkhäuser.
- Bauer, R., Düll, W.-P., & Schneider, G. (2019). The Korteweg--de Vries, Burgers and Whitham limits for a spatially periodic Boussinesq model. Proc. Roy. Soc. Edinburgh Sect. A, 149(1), 191--217. https://doi.org/10.1017/S0308210518000227
- Bhatt, A., Fehr, J., & Haasdonk, B. (2019). Model order reduction of an elastic body under large rigid motion. Proceedings of ENUMATH 2017, Lect. Notes Comput. Sci. Eng.,(126), Article 126. https://doi.org/10.1007/978-3-319-96415-7\_23
- Bhatt, A., Fehr, J., Grunert, D., & Haasdonk, B. (2019). A Posteriori Error Estimation in Model Order Reduction of Elastic Multibody Systems with Large Rigid Motion. In J. Fehr & B. Haasdonk (Hrsg.), IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. Springer. https://doi.org/DOI:10.1007/978-3-030-21013-7_7
- Bianchi, L. A., Blömker, D., & Schneider, G. (2019). Modulation equation and SPDEs on unbounded domains. Commun. Math. Phys., 371(1), 19--54.
- Brünnette, T., Santin, G., & Haasdonk, B. (2019). Greedy Kernel Methods for Accelerating Implicit Integrators for Parametric ODEs. In F. A. Radu, K. Kumar, I. Berre, J. M. Nordbotten, & I. S. Pop (Hrsg.), Numerical Mathematics and Advanced Applications - ENUMATH 2017 (S. 889--896). Springer International Publishing.
- Buchfink, P., Bhatt, A., & Haasdonk, B. (2019). Symplectic Model Order Reduction with Non-Orthonormal Bases. Mathematical and Computational Applications, 24(2), 43. https://doi.org/10.3390/mca24020043
- Carlberg, K., Brencher, L., Haasdonk, B., & Barth, A. (2019). Data-driven time parallelism via forecasting. SIAM Journal on Scientific Computing, 41(3), B466--B496.
- Chirilus-Bruckner, M., Maier, D., & Schneider, G. (2019). Diffusive stability for periodic metric graphs. Math. Nachr., 292(6), 1246--1259.
- Colombo, R. M., LeFloch, P. G., Rohde, C., & Trivisa, K. (2019). Nonlinear Hyperbolic Problems: Modeling, Analysis, and Numerics. Oberwohlfach Rep., 16, 1419–1497. https://www.ems-ph.org/journals/show_issue.php?issn=1660-8933&vol=16&iss=2
- Conlon, R., Degeratu, A., & Rochon, F. (2019). Quasi-asymptotically conical Calabi-Yau manifolds. Geom. Topol., 23(1), 29--100. https://doi.org/10.2140/gt.2019.23.29
- Defant, A., Mastyo, M., Sánchez-Pérez, E. A., & Steinwart, I. (2019). Translation invariant maps on function spaces over locally compact groups. J. Math. Anal. Appl., 470, 795--820. https://doi.org/10.1016/j.jmaa.2018.10.033
- Denzel, A., Haasdonk, B., & Kästner, J. (2019). Gaussian Process Regression for Minimum Energy Path Optimization and Transition State Search. J. Phys. Chem. A, 123(44), 9600--9611. https://doi.org/10.1021/acs.jpca.9b08239
- Engelke, S., de Fondeville, R., & Oesting, M. (2019). Extremal behaviour of aggregated data with an application to downscaling. Biometrika, 106(1), 127--144. https://doi.org/10.1093/biomet/asy052
- Farooq, M., & Steinwart, I. (2019). Learning Rates for Kernel-Based Expectile Regression. Mach. Learn., 108, 203--227. https://doi.org/10.1007/s10994-018-5762-9
- Föll, R., Haasdonk, B., Hanselmann, M., & Ulmer, H. (2019). Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation. https://openreview.net/forum?id=BkgosiRcKm
- Geck, M. (2019). Eigenvalues and Polynomial Equations. The American Mathematical Monthly, 126(10), 933--935. https://doi.org/10.1080/00029890.2019.1651168
- Griesemer, M., & Linden, U. (2019). Spectral theory of the Fermi polaron. Ann. Henri Poincaré, 20(6), 1931--1967. https://doi.org/10.1007/s00023-019-00796-1
- Hahn, B. N., & Kienle Garrido, M.-L. (2019). An efficient reconstruction approach for a class of dynamic imaging operators. Inverse Problems, 35(9), 094005. https://doi.org/10.1088/1361-6420/ab178b
- Hansmann, M., Kohler, M., & Walk, H. (2019). On the strong universal consistency of local averaging regression estimates (vol 71, pg 1233, 2019). ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 71(5), 1265–1269. https://doi.org/10.1007/s10463-018-0687-4
- Heil, K., & Jentsch, T. (2019). A special class of symmetric Killing 2-tensors. JOURNAL OF GEOMETRY AND PHYSICS, 138, 103–123. https://doi.org/10.1016/j.geomphys.2018.12.009
- Holicki, T., & Scherer, C. W. (2019). A Homotopy Approach for Robust Output-Feedback Synthesis. Proc. 27th. Med. Conf. Control Autom., 87–93. https://doi.org/10.1109/MED.2019.8798536
- Holicki, T., & Scherer, C. W. (2019). Stability Analysis and Output-Feedback Synthesis of Hybrid Systems Affected by Piecewise Constant Parameters via Dynamic Resetting Scalings. Nonlinear Anal. Hybri., 34, 179–208. https://doi.org/10.1016/j.nahs.2019.06.003
- Homma, Y., & Semmelmann, U. (2019). The Kernel of the Rarita-Schwinger Operator on Riemannian Spin Manifolds. Comm. Math. Phys., 370(3), 853--871. https://doi.org/10.1007/s00220-019-03324-8
- Höllig, K., & Hörner, J. (2019). Aufgaben und Lösungen zur Höheren Mathematik. - 1. [Aufgabensammlung]. In Aufgaben und Lösungen zur Höheren Mathematik ; 1 (2. Auflage, Bd. 1, S. x, 235 Seiten). Springer Spektrum.
- Kluth, T., Hahn, B. N., & Brandt, C. (2019). Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging. Proc. Int. Workshop Magnetic Particle Imaging.
- Kohr, M., & Wendland, W. L. (2019). 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, 131, 17–63. https://doi.org/10.1016/j.matpur.2019.04.002
- Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2019). Newtonian and Single Layer Potentials for the Stokes System with L∞ Coefficients and the Exterior Dirichlet Problem. In S. Rogosin & A. O. Celebi (Hrsg.), Analysis as a Life: Dedicated to Heinrich Begehr on the Occasion of his 80th Birthday (S. 237--260). Springer International Publishing. https://doi.org/10.1007/978-3-030-02650-9_12
- Kuhn, T., Dürrwächter, J., Meyer, F., Beck, A., Rohde, C., & Munz, C.-D. (2019). Uncertainty quantification for direct aeroacoustic simulations of cavity flows. J. Theor. Comput. Acoust., 27(1), 1850044, 20. https://doi.org/10.1142/S2591728518500445
- Köppel, M., Franzelin, F., Kröker, I., Oladyshkin, S., Santin, G., Wittwar, D., Barth, A., Haasdonk, B., Nowak, W., Pflüger, D., & Rohde, C. (2019). Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. Comput. Geosci., 2(23), 339–354. https://doi.org/10.1007/s10596-018-9785-x
- Mazzeo, R., Swoboda, J., Weiss, H., & Witt, F. (2019). Asymptotic geometry of the Hitchin metric. Commun. Math. Phys., 367(1), 151--191. https://doi.org/10.1007/s00220-019-03358-y
- Miller, C. T., Gray, W. G., Kees, C. E., Rybak, I. V., & Shepherd, B. J. (2019). Modeling sediment transport in three-phase surface water systems. J. Hydraul. Res., 57. https://doi.org/10.1080/00221686.2019.1581673
- Mücke, N., & Steinwart, I. (2019). Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning. Fakultät für Mathematik und Physik, Universität Stuttgart.
- Oesting, M., Schlather, M., & Schillings, C. (2019). Sampling sup-normalized spectral functions for Brown-Resnick processes. Stat, 8, e228, 11. https://doi.org/10.1002/sta4.228
- Ostrowski, L., & Massa, F. (2019). An incompressible-compressible approach for droplet impact. In G. Cossali & S. Tonini (Hrsg.), Proceedings of the DIPSI Workshop 2019: Droplet ImpactPhenomena & Spray Investigations, Bergamo, Italy, 17th May 2019 (S. 18–21). Università degli studi di Bergamo. https://doi.org/10.6092/DIPSI2019_pp18-21
- Rösinger, C. A., & Scherer, C. W. (2019). A Flexible Synthesis Framework of Structured Controllers for Networked Systems. IEEE Trans. Control Netw. Syst., 7(1), 6–18. https://doi.org/10.1109/TCNS.2019.2914411
- Rösinger, C. A., & Scherer, C. W. (2019). A Scalings Approach to $H_2$-Gain-Scheduling Synthesis without Elimination. IFAC-PapersOnLine, 52(28), 50–57. https://doi.org/10.1016/j.ifacol.2019.12.347
- Santin, G., & Haasdonk, B. (2019). Kernel Methods for Surrogate Modelling. University of Stuttgart.
- Santin, G., Wittwar, D., & Haasdonk, B. (2019). Sparse approximation of regularized kernel interpolation by greedy algorithms.
- Santin, G., & Haasdonk, B. (2019). Kernel Methods for Surrogate Modeling (ArXiv 1907.10556; Nummer 1907.10556). https://arxiv.org/abs/1907.10556
- Schanz, M., Wasser, C., Allgaeuer, S., Schricker, S., Dippon, J., Alscher, MD., & Kimmel, M. (2019). Urinary TIMP-2·IGFBP7-guided randomized controlled intervention trial to prevent acute kidney injury in the emergency department. Transplant., 2019 Nov 1;34(11), 1902–1909. https://doi.org/10.1093/ndt/gfy186
- Schmidt, A., Wittwar, D., & Haasdonk, B. (2019). Rigorous and effective a-posteriori error bounds for nonlinear problems -- Application to RB methods. Advances in Computational Mathematics. https://doi.org/10.1007/s10444-019-09730-9
- Schricker, S., Heider, T., Schanz, M., Dippon, J., Alscher, MD., Weiss, H., Mettang, T., & Kimmel, M. (2019). Strong Associations Between Inflammation, Pruritus and Mental Health in Dialysis Patients. Acta Derm Venereol., 2019 May 1;99(6), 524–529. https://doi.org/10.2340/00015555-3128
- Semmelmann, U., & Weingart, G. (2019). The standard Laplace operator. Manuscripta Math., 158(1–2), 273--293. https://doi.org/10.1007/s00229-018-1023-2
- Seus, D., Radu, F. A., & Rohde, C. (2019). A linear domain decomposition method for two-phase flow in porous media. Numerical Mathematics and Advanced Applications ENUMATH 2017, 603–614. https://doi.org/10.1007/978-3-319-96415-7_55
- Sharanya, V., Sekhar, G. P. R., & Rohde, C. (2019). Surfactant-induced migration of a spherical droplet in non-isothermal Stokes flow. Physics of Fluids, 31(1), 012110. https://doi.org/10.1063/1.5064694
- Steinwart, I. (2019). A Sober Look at Neural Network Initializations. Fakultät für Mathematik und Physik, Universität Stuttgart.
- Steinwart, I. (2019). Convergence Types and Rates in Generic Karhunen-Loève Expansions with Applications to Sample Path Properties. Potential Anal., 51, 361--395. https://doi.org/10.1007/s11118-018-9715-5
- Wenzel, T., Santin, G., & Haasdonk, B. (2019). A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution.
- Wittwar, D., Santin, G., & Haasdonk, B. (2019). Part II on matrix valued kernels including analysis.
- Wittwar, D., & Haasdonk, B. (2019). Greedy Algorithms for Matrix-Valued Kernels. In F. A. Radu, K. Kumar, I. Berre, J. M. Nordbotten, & I. S. Pop (Hrsg.), Numerical Mathematics and Advanced Applications ENUMATH 2017 (S. 113--121). Springer International Publishing.
- Zhang, R., Kyriss, T., Dippon, J., Boedeker, E., & Friedel, G. (2019). Preoperative serum lactate dehydrogenase level as a predictor of major omplications following thoracoscopic lobectomy: a propensity-adjusted analysis. European Journal of Cardio-Thoracic Surgery, 56(2), 294–300. https://doi.org/10.1093/ejcts/ezz027
- Zhang R, Dippon J, F. G. (2019). Refined risk stratification for thoracoscopic lobectomy or segmentectomy. Dis., J Thorac, 2019 Jan;11(1), :222-230. https://doi.org/10.21037/jtd.2018.12.44
2018
- Afkham, B. M., Bhatt, A., Haasdonk, B., & Hesthaven, J. S. (2018). Symplectic Model-Reduction with a Weighted Inner Product.
- Altenbernd, M., & Göddeke, D. (2018). Soft fault detection and correction for multigrid. The International Journal of High Performance Computing Applications, 32(6), 897–912. https://doi.org/10.1177/1094342016684006
- Barth, A., & Stein, A. (2018). A Study of Elliptic Partial Differential Equations with Jump Diffusion Coefficients. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 6(4), 1707–1743. https://doi.org/10.1137/17M1148888
- Barth, A., & Stüwe, T. (2018). Weak convergence of Galerkin approximations of stochastic partial differential equations driven by additive Lévy noise. Math. Comput. Simulation, 143, 215--225. https://doi.org/10.1016/j.matcom.2017.03.007
- Barth, A., & Stein, A. (2018). Approximation and simulation of infinite-dimensional Levy processes. STOCHASTICS AND PARTIAL DIFFERENTIAL EQUATIONS-ANALYSIS AND COMPUTATIONS, 6(2), 286–334. https://doi.org/10.1007/s40072-017-0109-2
- Bhatt, A., Fehr, J., Grunert, D., & Haasdonk, B. (2018). A Posteriori Error Estimation in Model Order Reduction of Elastic Multibody Systems with Large Rigid Motion. In J. Fehr & B. Haasdonk (Hrsg.), IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. Springer. https://doi.org/DOI:10.1007/978-3-030-21013-7_7
- Bhatt, A., & Haasdonk, B. (2018). Certified and structure-preserving model order reduction of EMBS. In RAMSA 2017, New Delhi.
- Bhatt, A., Haasdonk, B., & Moore, B. E. (2018). Structure-preserving Integration and Model Order Reduction. In Invited online talk in Department of Mathematics, IIT Roorkee.
- Blaschzyk, I., & Steinwart, I. (2018). Improved Classification Rates under Refined Margin Conditions. Electron. J. Stat., 12, 793--823. https://doi.org/10.1214/18-EJS1406
- Bradley, C. P., Emamy, N., Ertl, T., Göddeke, D., Hessenthaler, A., Klotz, T., Krämer, A., Krone, M., Maier, B., Mehl, M., Tobias, R., & Röhrle, O. (2018). Enabling Detailed, Biophysics-Based Skeletal Muscle Models on HPC Systems. Frontiers in Physiology, 9(816), Article 816. https://doi.org/10.3389/fphys.2018.00816
- Brehler, M., Schirwon, M., Göddeke, D., & Krummrich, P. (2018, Juli). Modeling the Kerr-Nonlinearity in Mode-Division Multiplexing Fiber Transmission Systems on GPUs. Proceedings of Advanced Photonics 2018.
- Brünnette, T., Santin, G., & Haasdonk, B. (2018). Greedy kernel methods for accelerating implicit integrators for parametric ODEs. Proceedings of ENUMATH 2017. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1767
- Buchfink, P. (2018). Structure-preserving Model Reduction for Elasticity [Diploma thesis].
- Chalons, C., Magiera, J., Rohde, C., & Wiebe, M. (2018). A finite-volume tracking scheme for two-phase compressible flow. Springer Proc. Math. Stat., 309--322. https://doi.org/10.1007/978-3-319-91545-6_25
- De Marchi, S., Iske, A., & Santin, G. (2018). Image reconstruction from scattered Radon data by weighted positive definite kernel functions. Calcolo, 55(1), 2. https://doi.org/10.1007/s10092-018-0247-6
- de Rijk, B. (2018). Spectra and stability of spatially periodic pulse patterns II: the critical spectral curve. SIAM J. Math. Anal., 50(2), 1958--2019. https://doi.org/10.1137/17M1127594
- de Rijk, B., & Sandstede, B. (2018). Diffusive stability against nonlocalized perturbations of planar wave trains in reaction-diffusion systems. J. Differential Equations, 265(10), 5315--5351. https://doi.org/10.1016/j.jde.2018.07.011
- Degeratu, A., & Mazzeo, R. (2018). Fredholm theory for elliptic operators on quasi-asymptotically conical spaces. Proc. Lond. Math. Soc. (3), 116(5), 1112--1160. https://doi.org/10.1112/plms.12105
- Devroye, L., Gyorfi, L., Lugosi, G., & Walk, H. (2018). A nearest neighbor estimate of the residual variance. ELECTRONIC JOURNAL OF STATISTICS, 12(1), 1752–1778. https://doi.org/10.1214/18-EJS1438
- Dibak, C., Haasdonk, B., Schmidt, A., Dürr, F., & Rothermel, K. (2018). Enabling interactive mobile simulations through distributed reduced models. Pervasive and Mobile Computing, Elsevier BV, 45, 19--34. https://doi.org/10.1016/j.pmcj.2018.02.002
- Doelman, A., Rademacher, J., de Rijk, B., & Veerman, F. (2018). Destabilization Mechanisms of Periodic Pulse Patterns Near a Homoclinic Limit. SIAM J. Appl. Dyn. Syst., 17(2), 1833--1890. https://doi.org/10.1137/17M1122840
- Doering, M., Gyorfi, L., & Walk, H. (2018). Rate of Convergence of k-Nearest-Neighbor Classification Rule. JOURNAL OF MACHINE LEARNING RESEARCH, 18.
- Düll, W.-P., & Heß, M. (2018). Existence of long time solutions and validity of the nonlinear Schrödinger approximation for a quasilinear dispersive equation. J. Differential Equations, 264(4), 2598--2632. https://doi.org/10.1016/j.jde.2017.10.031
- Düll, W.-P., Hilder, B., & Schneider, G. (2018). Analysis of the embedded cell method in 1D for the numerical homogenization of metal-ceramic composite materials. J. Appl. Anal., 24(1), 71--80.
- Düll, W.-P. (2018). On the mathematical description of time-dependent surface water waves. Jahresber. Dtsch. Math.-Ver., 120(2), 117--141. https://doi.org/10.1365/s13291-017-0173-6
- Dürrwächter, J., Kuhn, T., Meyer, F., Schlachter, L., & Schneider, F. (2018). A hyperbolicity-preserving discontinuous stochastic Galerkin scheme for uncertain hyperbolic systems of equations. Journal of Computational and Applied Mathematics, 112602. https://doi.org/10.1016/j.cam.2019.112602
- Engwer, C., Altenbernd, M., Dreier, N.-A., & Göddeke, D. (2018, März). A high-level C++ approach to manage local errors, asynchrony and faults in an MPI application. Proceedings of the 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2018).
- Fechter, S., Munz, C.-D., Rohde, C., & Zeiler, C. (2018). Approximate Riemann solver for compressible liquid vapor flow with phase transition and surface tension. Comput. & Fluids, 169, 169–185. http://dx.doi.org/10.1016/j.compfluid.2017.03.026
- Fehr, J., Grunert, D., Bhatt, A., & Haasdonk, B. (2018). A Sensitivity Study of Error Estimation in Reduced Elastic Multibody Systems. Proceedings of MATHMOD 2018, Vienna, Austria.
- Fritz, P., Dippon, J., Müller, S., Goletz, S., Trautmann, C., Pappas, X., Ott, G., Brauch, H., Schwab, M., Winter, S., Mürdter, T., Brinkmann, F., Faisst, S., Rössle, S., Gerteis, A., & Friedel, G. (2018). Is Mistletoe Treatment Beneficial in Invasive Breast Cancer? A New Approach to an Unresolved Problem. Anticancer research, 38(3), 1585–1593. https://doi.org/10.21873/anticanres.12388
- Fritzen, F., Haasdonk, B., Ryckelynck, D., & Schöps, S. (2018). An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem. Math. Comput. Appl. 2018, 23(1), Article 1. https://doi.org/doi:10.3390/mca23010008
- Geck, M. (2018). On the values of unipotent characters in bad characteristic. Rendiconti del Seminario Matematico della Università di Padova, 141, 37--63. https://doi.org/10.4171/rsmup/14
- Geck, M. (2018). A first guide to the character theory of finite groups of Lie type. Local Representation Theory and Simple Groups (eds. R. Kessar, G. Malle, D. Testerman), 63--106. https://doi.org/10.4171/185-1/3
- Georgiev, V., & Wirth, J. (2018). Zero resonances for localised potentials. Journal of Mathematical Physics, 59(7), 071502. https://doi.org/10.1063/1.5027717
- Giesselmann, J., Kolbe, N., Lukacova-Medvidova, M., & Sfakianakis, N. (2018). Existence and uniqueness of global classical solutions to a two species cancer invasion haptotaxis model. Accepted for publication in Discrete Contin. Dyn. Syst. Ser. B. https://arxiv.org/abs/1704.08208
- Gimperlein, H., Meyer, F., Özdemir, C., & Stephan, E. P. (2018). Time domain boundary elements for dynamic contact problems. Computer Methods in Applied Mechanics and Engineering, 333, 147–175. https://doi.org/10.1016/j.cma.2018.01.025
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- Langer, A. (2017). Automated Parameter Selection in the L1-L2-TV Model for Removing Gaussian Plus Impulse Noise. Inverse Problems, 33, 41. http://people.ricam.oeaw.ac.at/a.langer/publications/L1L2TVm.pdf
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- Düll, W.-P., Kashani, K. S., & Schneider, G. (2016). The validity of Whitham’s approximation for a Klein-Gordon-Boussinesq model. SIAM J. Math. Anal., 48(6), 4311--4334. https://doi.org/10.1137/16M1071687
- Düll, W.-P., Schneider, G., & Wayne, C. E. (2016). Justification of the nonlinear Schrödinger equation for the evolution of gravity driven 2D surface water waves in a canal of finite depth. Arch. Ration. Mech. Anal., 220(2), 543--602. https://doi.org/10.1007/s00205-015-0937-z
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- Kohr, M., de Cristoforis, M. L., & Wendland, W. L. (2016). On the Robin-Transmission Boundary Value Problems for the Nonlinear Darcy-Forchheimer-Brinkman and Navier-Stokes Systems. JOURNAL OF MATHEMATICAL FLUID MECHANICS, 18(2), 293–329. https://doi.org/10.1007/s00021-015-0236-3
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- Magiera, J., Rohde, C., & Rybak, I. (2016). A hyperbolic-elliptic model problem for coupled surface-subsurface flow. Transp. Porous Media, 114, 425–455. https://doi.org/10.1007/S11242-015-0548-Z
- Meister, M., & Steinwart, I. (2016). Optimal Learning Rates for Localized SVMs. J. Mach. Learn. Res., 17, 1–44.
- Nguyen Tien, H., Scherer, C. W., Scherpen, J. M. A., & Müller, V. (2016). Linear Parameter Varying Control of Doubly Fed Induction Machines. IEEE Trans. Ind. Electron., 63(1), 216–224. https://doi.org/10.1109/TIE.2015.2465895
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- Redeker, M., & Haasdonk, B. (2016). A POD-EIM reduced two-scale model for precipitation in porous media. MATHEMATICAL AND COMPUTER MODELLING OF DYNAMICAL SYSTEMS, 20(4), 323–344. https://doi.org/10.1080/13873954.2016.1198384
- Rossi, E., & Schleper, V. (2016). Convergence of a numerical scheme for a mixed hyperbolic-parabolic system in two space dimensions. ESAIM Math. Model. Numer. An., 50(2), 475–497. https://doi.org/10.1051/m2an/2015050
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- Scherer, C. W. (2016). Lossless $H_ınfty$-synthesis for 2D systems (special issue JCW). Syst. Control Lett., 95, 25–35. https://doi.org/10.1016/j.sysconle.2016.02.011
- Schleper, V. (2016). A HLL-type Riemann solver for two-phase flow with surface forces and phase transitions. Appl. Numer. Math., 108, 256–270. https://doi.org/10.1016/j.apnum.2015.12.010
- Schmidt, A., & Haasdonk, B. (2016). Reduced basis method for H2 optimal feedback control problems. IFAC-PapersOnLine, 49(8), 327–332. http://dx.doi.org/10.1016/j.ifacol.2016.07.462
- Schneider, G. (2016). Validity and non-validity of the nonlinear Schrödinger equation as a model for water waves. In Lectures on the theory of water waves. Papers from the talks given at the Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, July -- August, 2014 (S. 121--139). Cambridge: Cambridge University Press.
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- Trottemant, E. J., Scherer, C. W., & Mazo, M. (2016). Optimality of robust disturbance-feedback strategies. Int. J. Robust Nonlin., 26(7), 1475–1488. https://doi.org/10.1002/rnc.3360
- Trottemant, E. J., Mazo, M., & Scherer, C. W. (2016). Synthesis of Robust Piecewise Affine Output-Feedback Strategies. J. Guid. Control Dynam., 39(7), 1461–1469. https://doi.org/10.2514/1.G001343
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2015
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- Allerhand, L. I., Gershon, E., & Shaked, U. (2015). State-feedback Control of Stochastic Discrete-time Linear Switched Systems with Dwell Time. Eur. Control Conf., 452–457. https://doi.org/10.1109/ECC.2015.7330585
- Allerhand, L. I. (2015). Stability of adaptive control in the presence of input disturbances and $H_ınfty$ performance. IFAC-PapersOnLine, 48(14), 76–81. https://doi.org/10.1016/j.ifacol.2015.09.437
- Amsallem, D., & Haasdonk, B. (2015). PEBL-ROM: Projection-Error Based Local Reduced-Order Models [SimTech Preprint]. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1436
- Amsallem, D., Farhat, C., & Haasdonk, B. (2015). Editorial: Special Issue on Model Reduction. IJNME, International Journal of Numerical Methods in Engineering, 102(5), 931--932. https://doi.org/10.1002/nme.4889
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- Garmatter, D., Haasdonk, B., & Harrach, B. (2015). A reduced Landweber Method for Nonlinear Inverse Problems. University of Stuttgart.
- Geck, M., & Bonnafe, C. (2015). Hecke algebras with unequal parameters and Vogan’s left cell invariants. Representations of reductive groups. In Honor of the 60th birthday of David A. Vogan, Jr (eds. M. Nevins and P. Trapa), 312, 173--188. https://doi.org/10.1007/978-3-319-23443-4_6
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- Giesselmann, J. (2015). Low Mach asymptotic preserving scheme for the Euler-Korteweg model. IMA J. Numer. Anal., 35(2), 802--832. https://doi.org/10.1093/imanum/dru022
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- Giesselmann, J., Makridakis, C., & Pryer, T. (2015). A posteriori analysis of discontinuous Galerkin schemes for systems of hyperbolic conservation laws. SIAM J. Numer. Anal., 53, 1280--1303. http://dx.doi.org/10.1137/140970999
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- Kohr, M., Pintea, C., & Wendland, W. L. (2015). Poisson-Transmission Problems for -Perturbations of the Stokes System on Lipschitz Domains in Compact Riemannian Manifolds. JOURNAL OF DYNAMICS AND DIFFERENTIAL EQUATIONS, 27(3–4), 823–839. https://doi.org/10.1007/s10884-014-9359-0
- Kohr, M., de Cristoforis, M. L., & Wendland, W. L. (2015). Poisson problems for semilinear Brinkman systems on Lipschitz domains in R-n. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND PHYSIK, 66(3), 833–864. https://doi.org/10.1007/s00033-014-0439-0
- Kovarik, H., & Weidl, T. (2015). Improved Berezin-Li-Yau inequalities with magnetic field. In Proceedings of the Royal Society Of Edinburgh. Section A, Mathematics (Nr. 1; Bd. 145, Nummer 1, S. 145–160). Cambridge Univ. Press. https://doi.org/10.1017/S0308210513001595
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- Kröker, I., Nowak, W., & Rohde, C. (2015). A stochastically and spatially adaptive parallel scheme for uncertain and nonlinear two-phase flow problems. Comput. Geosci., 19(2), 269--284. https://doi.org/10.1007/s10596-014-9464-5
- Kutter, M. (2015). A two scale model for liquid phase epitaxy with elasticity [University of Stuttgart]. http://elib.uni-stuttgart.de/opus/volltexte/2015/9833/
- Köroglu, H., Scherer, C. W., & Falcone, P. (2015). Robust Static Output Feedback Synthesis under an Integral Quadratic Constraint on the States. Eur. Control Conf., 3203–3208. https://doi.org/10.1109/ECC.2015.7331027
- List, F., & Radu, F. A. (2015). A study on iterative methods for solving Richards’ equation. http://www.nupus.uni-stuttgart.de/07_Preprints_Publications/Preprints/Preprints-PDFs/Preprint_201506.pdf
- Martini, I., & Haasdonk, B. (2015). Output Error Bounds for the Dirichlet-Neumann Reduced Basis Method. Numerical Mathematics and Advanced Applications - ENUMATH 2013, 103, 437--445. https://doi.org/10.1007/978-3-319-10705-9_43
- Martini, I., Rozza, G., & Haasdonk, B. (2015). Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system. Advances in Computational Mathematics, 41(5), 1131--1157. https://doi.org/10.1007/s10444-014-9396-6
- Micula, S., & Wendland, W. L. (2015). Trigonometric collocation for nonlinear Riemann-Hilbert problems in doubly connected domains. IMA J. Num. Analysis, 35, 834–858.
- Micula, S., & Wendland, W. L. (2015). Trigonometric collocation for nonlinear Riemann-Hilbert problems on doubly connected domains. IMA JOURNAL OF NUMERICAL ANALYSIS, 35(2), 834–858. https://doi.org/10.1093/imanum/dru009
- Missler, J., Schwarzmann, D., & Allerhand, L. I. (2015). On the Influence of Filter Choice in Output-Feedback MRAC during Adaptation Transients. IFAC-PapersOnLine, 48(11), 505–510. https://doi.org/10.1016/j.ifacol.2015.09.236
- Müthing, S., Ribbrock, D., & Göddeke, D. (2015). Integrating multi-threading and accelerators into DUNE-ISTL. In A. Abdulle, S. Deparis, D. Kressner, F. Nobile, & M. Picasso (Hrsg.), Numerical Mathematics and Advanced Applications -- ENUMATH 2013 (Bd. 103, S. 601--609). Springer. https://doi.org/10.1007/978-3-319-10705-9_59
- Neusser, J., Rohde, C., & Schleper, V. (2015). Relaxation of the Navier-Stokes-Korteweg Equations for Compressible Two-Phase Flow with Phase Transition. J. Numer. Methods Fluids, 79, 615–639. https://doi.org/10.1002/fld.4065
- Neusser, J., Rohde, C., & Schleper, V. (2015). Relaxed Navier-Stokes-Korteweg Equations for compressible two-phase flow with phase transition. J. Numer. Meth. Fluids, 79(12), 615–639. https://doi.org/10.1002/fld.4065
- Neusser, J., & Schleper, V. (2015). Numerical schemes for the coupling of compressible and incompressible fluids in several space dimensions.
- Oztepe, G. S., Choudhury, S. R., & Bhatt, A. (2015). Multiple Scales and Energy Analysis of Coupled Rayleigh-Van der Pol Oscillators with Time-Delayed Displacement and Velocity Feedback: Hopf Bifurcations and Amplitude Death. Far East Journal of Dynamical Systems. https://doi.org/10.17654/FJDSMar2015_031_059
- Redeker, M., & Haasdonk, B. (2015). A POD-EIM reduced two-scale model for precipitation in porous media [SimTech Preprint]. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=964
- Redeker, M., & Haasdonk, B. (2015). A POD-EIM reduced two-scale model for crystal growth. Advances in Computational Mathematics, 41(5), 987--1013. https://doi.org/10.1007/s10444-014-9367-y
- Rohde, C., & Zeiler, C. (2015). A relaxation Riemann solver for compressible two-phase flow with phase transition and surface tension. APPLIED NUMERICAL MATHEMATICS, 95(SI), 267–279. https://doi.org/10.1016/j.apnum.2014.05.001
- Ruzhansky, M., & Wirth, J. (2015). L-p Fourier multipliers on compact Lie groups. Math. Z., 280(3–4), 621--642. https://doi.org/10.1007/s00209-015-1440-9
- Rybak, I. V., Gray, W. G., & Miller, C. T. (2015). Modeling two-fluid-phase flow and species transport in porous media. J. Hydrology, 521, 565--581. https://doi.org/10.1016/j.jhydrol.2014.11.051
- Rybak, I., Magiera, J., Helmig, R., & Rohde, C. (2015). Multirate time integration for coupled saturated/unsaturated porous medium and free flow systems. Comput. Geosci., 19, 299–309. https://doi.org/10.1007/s10596-015-9469-8
- Scherer, C. W. (2015). Gain-scheduling control with dynamic multipliers by convex optimization. SIAM J. Contr. Optim., 53(3), 1224–1249. https://doi.org/10.1137/140985871
- Schleper, V. (2015). A hybrid model for traffic flow and crowd dynamics with random individual properties. Math. Biosci. Eng., 12(2), 393–413. https://doi.org/10.3934/mbe.2015.12.393
- Schleper, V. (2015). Nonlinear Transport and Coupling of Conservation Laws.
- Schmidt, A., Dihlmann, M., & Haasdonk, B. (2015). Basis generation approaches for a reduced basis linear quadratic regulator. Proc. MATHMOD 2015 - 8th Vienna International Conference on Mathematical Modelling, 713--718. https://doi.org/10.1016/j.ifacol.2015.05.016
- Schmidt, A., & Haasdonk, B. (2015). Reduced basis method for $H_2$ optimal feedback control problems. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1442
- Schmidt, A., & Haasdonk, B. (2015). Reduced Basis Approximation of Large Scale Algebraic Riccati Equations. University of Stuttgart.
- Steinwart, I. (2015). Supplement B to ``Fully Adaptive Density-Based Clustering’’. Fakultät für Mathematik und Physik, Universität Stuttgart. https://doi.org/10.1214/15-AOS1331SUPP
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2014
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