Publikationen des Fachbereichs Mathematik

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, Article 31. 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

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

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

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, 105039. 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

Eggenweiler, E., Discacciati, M., & Rybak, I. (2021). Analysis of the Stokes-Darcy problem with generalised interface conditions. ESAIM Math. Model. Numer. Anal. (submitted). https://arxiv.org/abs/2104.02339

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

Frank, R. L., Laptev, A., & Weidl, T. (2021). Lieb-Thirring Inequalities.

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). Non-overlapping Schwarz Waveform-Relaxation for Nonlinear Advection-Diffusion Equations. http://www.uhasselt.be/Documents/CMAT/Preprints/2021/UP2103.pdf

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., Wenzel, T., Santin, G., & Schmitt, S. (2021). Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. In F. J. Vermolen & C. Vuik (Hrsg.), Numerical Mathematics and Advanced Applications ENUMATH 2019 (S. 499--508). Springer International Publishing.

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., & 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

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

Kollross, A. (2021). Polar actions on Damek-Ricci spaces. Differential Geometry and its Applications, 76, 101753. https://doi.org/10.1016/j.difgeo.2021.101753

Krämer, A., Maier, B., Rau, T., Huber, F., Klotz, T., Ertl, T., Göddeke, D., Mehl, M., Reina, G., & Röhrle, O. (2021). Multi-physics multi-scale HPC simulations of skeletal muscles. In W. E. Nagel, D. H. Kröner, & M. M. Resch (Hrsg.), High Performance Computing in Science and Engineering ’20: Transactions of the High Performance Computing Center, Stuttgart(HLRS) 2020. https://doi.org/10.1007/978-3-030-80602-6_13

Kühnert, J., Göddeke, D., & Herschel, M. (2021, Juli). Provenance-integrated parameter selection and optimization in numerical simulations. 13th International Workshop on Theory and Practice ofProvenance (TaPP 2021). https://www.usenix.org/conference/tapp2021/presentation/kühnert

Lang, R. (2021). On the eigenvalues of the non-self-adjoint Robin Laplacian on bounded domains and compact quantum graphs. [Dissertation, Universität Stuttgart]. https://doi.org/10.18419/opus-11428

Magiera, J. (2021). A Molecular--Continuum Multiscale Solver for Liquid--Vapor Flow. Small Collaboration: Advanced Numerical Methods for Nonlinear Hyperbolic Balance Laws and Their Applications (hybrid meeting), 41. https://doi.org/10.14760/OWR-2021-41

Magiera, J., & Rohde, C. (2021). Analysis and Numerics of Sharp and Diffuse Interface Models for Droplet Dynamics. In K. Schulte, C. Tropea, & B. Weigand (Hrsg.), submitted to Droplet Dynamics under Extreme Ambient Conditions. Springer.

Magiera, J. (2021). A Molecular--Continuum Multiscale Solver for Liquid--Vapor Flow: Modeling and Numerical Simulation [Ph.D. Thesis]. https://doi.org/10.18419/opus-11797

Makogin, V., Oesting, M., Rapp, A., & Spodarev, E. (2021). Long range dependence for stable random processes. J. Time Series Anal., 42(2), 161--185. https://doi.org/10.1111/jtsa.12560

Massa, F., Ostrowski, L., Bassi, F., & Rohde, C. (2021). 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

Miao, Y., Rohde, C., & Tang, H. (2021). Well-posedness for a stochastic Camassa-Holm type equation with higher order nonlinearities. https://arxiv.org/abs/2105.08607

Mohammadi, F., Eggenweiler, E., Flemisch, B., Oladyshkin, S., Rybak, I., Schneider, M., & Weishaupt, K. (2021). Uncertainty-aware Validation Benchmarks for Coupling Free Flow and Porous-Medium Flow. Water Resour. Res. (preprint). https://arxiv.org/abs/2106.13639

Nonnenmacher, M., Reeb, D., & Steinwart, I. (2021). Which Minimizer Does My Neural Network Converge To? In N. Oliver, F. Pérez-Cruz, S. Kramer, J. Read, & J. A. Lozano (Hrsg.), Joint European Conference on Machine Learning and Knowledge Discovery in Databases (S. 87--102). Springer International Publishing. https://doi.org/10.1007/978-3-030-86523-8_6

Osorno, M., Schirwon, M., Kijanski, N., Sivanesapillai, R., Steeb, H., & Göddeke, D. (2021). A cross-platform, high-performance SPH toolkit for image-based flow simulations on the pore scale of porous media. Computer Physics Communications, 267(108059), Article 108059. https://doi.org/10.1016/j.cpc.2021.108059

Rohde, C., & von Wolff, L. (2021). A Ternary Cahn-Hilliard-Navier-Stokes model for two phase flow with precipitation and dissolution. Math. Models Methods Appl. Sci., 31(1), 1--35. https://doi.org/10.1142/S0218202521500019

Rohde, C., & Tang, H. (2021). On the stochastic Dullin-Gottwald-Holm equation: global existence and wave-breaking phenomena. NoDEA Nonlinear Differential Equations Appl., 28(1), Paper No. 5, 34. https://doi.org/10.1007/s00030-020-00661-9

Rohde, C., & Tang, H. (2021). On a stochastic Camassa-Holm type equation with higher order nonlinearities. J Dyn Diff Equat, 33, 1823–1852. https://doi.org/10.1007/s10884-020-09872-1

Rybak, I., Schwarzmeier, C., Eggenweiler, E., & Rüde, U. (2021). Validation and calibration of coupled porous-medium and free-flow problems using pore-scale resolved models. Comput. Geosci., 25, 621–635. https://doi.org/10.1007/s10596-020-09994-x

Rörich, A., Werthmann, T. A., Göddeke, D., & Grasedyck, L. (2021). Bayesian inversion for electromyography using low-rank tensor formats. Inverse Problems, 37(5), 055003. https://doi.org/10.1088/1361-6420/abd85a

Schricker, S., Monje, DC., Dippon, J., Kimmel, M., Alscher, MD., & Schanz, M. (2021). Physician-guided, hybrid genetic testing exerts promising effects on health-related behavior without compromising quality of life. Sci Rep., 2021 Apr 19;11(1), 8494. https://doi.org/10.1038/s41598-021-87821-8

Seus, D., Radu, F. A., & Rohde, C. (2021). Towards Hybrid Two-Phase Modelling Using Linear Domain Decomposition. https://arxiv.org/abs/2106.14247

Stauch, G., Fritz, P., Rokai, R., Sediqi, A., Firooz, H., Voelker, HU., Weinhara, M., Mollin, J., Soudah, B., Dalquen, P., Brinckmann, F., & Dippon, J. (2021). The Importance of Clinical Data for the Diagnosis of Breast Tumours in North Afghanistan. Int. Jounal Breast Cancer, Jul 30;2021, 6625239. https://doi.org/10.1155/2021/6625239

Steinwart, I., & Fischer, S. (2021). A Closer Look at Covering Number Bounds for Gaussian Kernels. J. Complexity, 62, 101513. https://doi.org/10.1016/j.jco.2020.101513

Steinwart, I., & Ziegel, J. F. (2021). Strictly proper kernel scores and characteristic kernels on compact spaces. Appl. Comput. Harmon. Anal., 51, 510--542. https://doi.org/10.1016/j.acha.2019.11.005

Strohbeck, P., Eggenweiler, E., & Rybak, I. (2021). Determination of the Beavers-Joseph slip coefficient for coupled Stokes/Darcy problems. Adv. Water Res. (submitted). https://arxiv.org/abs/2106.15556

Veenman, J., Scherer, C. W., Ardura, C., Bennani, S., Preda, V., & Girouart, B. (2021). IQClab: A new IQC based toolbox for robustness analysis and control design. IFAC-PapersOnline, 54(8), 69--74. https://doi.org/10.1016/j.ifacol.2021.08.583

von Wolff, L., Weinhardt, F., Class, H., Hommel, J., & Rohde, C. (2021). Investigation of Crystal Growth in Enzymatically Induced Calcite Precipitation by Micro-Fluidic Experimental Methods and Comparison with Mathematical Modeling. Transp. Porous Media, 137(2), 327--343. https://doi.org/10.1007/s11242-021-01560-y

Wagner, A., Eggenweiler, E., Weinhardt, F., Trivedi, Z., Krach, D., Lohrmann, C., Jain, K., Karadimitriou, N., Bringedal, C., Voland, P., Holm, C., Class, H., Steeb, H., & Rybak, I. (2021). Permeability estimation of regular porous structures: a benchmark for comparison of methods. Transp. Porous Med. https://doi.org/10.1007/s11242-021-01586-2

Wenzel, T., Santin, G., & Haasdonk, B. (2021). A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution. Journal of Approximation Theory, 262, 105508. https://doi.org/10.1016/j.jat.2020.105508

Armiti-Juber, A., & Rohde, C. (2020). On the well-posedness of a nonlinear fourth-order extension of Richards’ equation. J. Math. Anal. Appl., 487(2), 124005. https://doi.org/10.1016/j.jmaa.2020.124005

Barberis, M. L., Moroianu, A., & Semmelmann, U. (2020). Generalized vector cross products and Killing forms on negatively curved manifolds. Geom. Dedicata, 205, 113--127. https://doi.org/10.1007/s10711-019-00467-9

Barreau, M., Scherer, C. W., Gouaisbaut, F., & Seuret, A. (2020). Integral Quadratic Constraints on Linear Infinite-dimensional Systems for Robust Stability Analysis. IFAC World Congress.

Barth, A., & Merkle, R. (2020). Subordinated Gaussian Random Fields in Elliptic Partial Differential Equations. ArXiv e-prints, arXiv:2011.09311 math.NA.

Barth, A., & Merkle, R. (2020). Subordinated Gaussian Random Fields. ArXiv e-prints, arXiv:2012.06353 math.PR.

Bastian, P., Altenbernd, M., Dreier, N.-A., Engwer, C., Fahlke, J., Fritze, R., Geveler, M., Göddeke, D., Iliev, O., Ippisch, O., Mohring, J., Müthing, S., Ohlberger, M., Ribbrock, D., Shegunov, N., & Turek, S. (2020). Exa-Dune - Flexible PDE Solvers, Numerical Methods and Applications. In H.-J. Bungartz, S. Reiz, B. Uekermann, P. Neumann, & W. E. Nagel (Hrsg.), Software for Exascale Computing -- SPPEXA 2016--2019 (S. 225--269). Springer. https://doi.org/10.1007/978-3-030-47956-5_9

Baumstark, S., Schneider, G., Schratz, K., & Zimmermann, D. (2020). Effective slow dynamics models for a class of dispersive systems. J. Dyn. Differ. Equations, 32(4), 1867--1899.

Baumstark, S., Schneider, G., & Schratz, K. (2020). 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 (S. 37--48). Cham: Birkhäuser.

Beck, A., Dürrwächter, J., Kuhn, T., Meyer, F., Munz, C.-D., & Rohde, C. (2020). $hp$-Multilevel Monte Carlo methods for uncertainty quantification of compressible flows. SIAM J. Sci. Comput., 42(4), B1067–B1091. https://doi.org/10.1137/18M1210575

Berberich, J., Koch, A., Scherer, C. W., & Allgöwer, F. (2020). Robust data-driven state-feedback design. 2020 American Control Conference (ACC), 1532–1538. https://doi.org/10.23919/acc45564.2020.9147320

Berre, I., Boon, W. M., Flemisch, B., Fumagalli, A., Gläser, D., Keilegavlen, E., Scotti, A., Stefansson, I., Tatomir, A., Brenner, K., Burbulla, S., Devloo, P., Duran, O., Favino, M., Hennicker, J., Lee, I.-H., Lipnikov, K., Masson, R., Mosthaf, K., … Zulian, P. (2020). Verification benchmarks for single-phase flow in three-dimensional fractured porous media.

Bitter, A. (2020). Virtual levels of multi-particle quantum systems and their implications for the Efimov effect [Dissertation, Universität Stuttgart]. https://doi.org/10.18419/opus-11315

Blanke, S. E., Hahn, B. N., & Wald, A. (2020). Inverse problems with inexact forward operator: iterative regularization and application in dynamic imaging. Inverse Problems, 36(12), 124001. https://doi.org/10.1088/1361-6420/abb5e1

Brehler, M., Schirwon, M., Krummrich, P. M., & Göddeke, D. (2020). Simulation of Nonlinear Signal Propagation in Multimode Fibers on Multi-GPU Systems. Communications in Nonlinear Science and Numerical Simulation, 84, 105150. https://doi.org/10.1016/j.cnsns.2019.105150

Brinker, J., & Wirth, J. (2020). Gelfand Triples for the Kohn–Nirenberg Quantization on Homogeneous Lie Groups. In Advances in Harmonic Analysis and Partial Differential Equations. (S. 51–97). Birkhäuser. https://doi.org/10.1007/978-3-030-58215-9_3

Buchfink, P., Haasdonk, B., & Rave, S. (2020). PSD-Greedy Basis Generation for Structure-Preserving Model Order Reduction of Hamiltonian Systems. In P. Frolkovič, K. Mikula, & D. Ševčovič (Hrsg.), Proceedings of the Conference Algoritmy 2020 (S. 151--160). Vydavateľstvo SPEKTRUM. http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/1577/829

Burbulla, S., & Rohde, C. (2020). A fully conforming finite volume approach to two-phase flow in fractured porous media. In R. Klöfkorn, E. Keilegavlen, F. A. Radu, & J. Fuhrmann (Hrsg.), Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples (S. 547–555). Springer International Publishing. https://doi.org/10.1007/978-3-030-43651-3_51

de Rijk, B., & Schneider, G. (2020). Global Existence and Decay in Nonlinearly Coupled Reaction-Diffusion-Advection Equations with Different Velocities. J. Differential Equations, 268(7), 3392--3448. https://doi.org/10.1016/j.jde.2019.09.056

Díaz-Ramos, J. C., Domínguez-Vázquez, M., & Kollross, A. (2020). On homogeneous manifolds whose isotropy actions are polar. manuscripta mathematica, 161(1), 15--34. https://doi.org/10.1007/s00229-018-1077-1

Eggenweiler, E., & Rybak, I. (2020). Unsuitability of the Beavers-Joseph interface condition for filtration problems. J. Fluid Mech., 892, A10. http://dx.doi.org/10.1017/jfm.2020.194

Eggenweiler, E., & Rybak, I. (2020). Interface conditions for arbitrary flows in coupled porous-medium and free-flow systems. In R. Klöfkorn, E. Keilegavlen, F. Radu, & J. Fuhrmann (Hrsg.), Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples (Bd. 323, S. 345--353). Springer International Publishing. https://doi.org/10.1007/978-3-030-43651-3_31

Fischer, S., & Steinwart, I. (2020). Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm. J. Mach. Learn. Res., 205, 1--38.

Fischer, S., & Steinwart, I. (2020). Sobolev norm learning rates for regularized least-squares algorithms. J. Mach. Learn. Res., 21(205), 1--38. http://jmlr.org/papers/v21/19-734.html

Geck, M. (2020). Green functions and Glauberman degree-divisibility. Annals of Mathematics, 192(1), 229–249. https://doi.org/10.4007/annals.2020.192.1.4

Geck, M. (2020). On Jacob’s construction of the rational canonical form of a matrix. The Electronic Journal of Linear Algebra, 36(36), 177--182. https://doi.org/10.13001/ela.2020.5055

Geck, M., & Malle, G. (2020). The character theory of finite groups of Lie type. A guided tour. In Cambridge Studies in Advanced Mathematics (Bd. 187, S. ix+394). Cambridge University Press. https://doi.org/10.1017/9781108779081

Geck, M. (2020). ChevLie: Constructing Lie algebras and Chevalley groups. Journal of Software for Algebra and Geometry, 10(1), 41--49. https://doi.org/10.2140/jsag.2020.10.41

Geck, M. (2020). Computing Green functions in small characteristic. Journal of Algebra, 561, 163--199. https://doi.org/10.1016/j.jalgebra.2019.12.016

Advances in Harmonic Analysis and Partial Differential Equations. (2020). In V. Georgiev, T. Ozawa, M. Ruzhansky, & J. Wirth (Hrsg.), Trends in Mathematics. Birkhäuser. https://doi.org/10.1007/978-3-030-58215-9

Gerstenberger, J. T., Burbulla, S., & Kröner, D. (2020). Discontinuous Galerkin method for incompressible two-phase flows. In R. Klöfkorn, E. Keilegavlen, F. A. Radu, & J. Fuhrmann (Hrsg.), Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples (S. 675–683). Springer International Publishing.

Giesselmann, J., Meyer, F., & Rohde, C. (2020). A posteriori error analysis for random scalar conservation laws using the Stochastic Galerkin method. IMA J. Numer. Anal., 40(2), 1094–1121. https://doi.org/10.1093/imanum/drz004

Giesselmann, J., Meyer, F., & Rohde, C. (2020). An a posteriori error analysis based on non-intrusive spectral projections for systems of random conservation laws. In A. Bressan, M. Lewicka, D. Wang, & Y. Zheng (Hrsg.), accepted for publication in Proceedings of HYP2018 (Bd. 10, S. 449–456). AIMS Series on Applied Mathematics. https://www.aimsciences.org/fileAIMS/cms/news/info/upload//c0904f1f-97d5-451f-b068-25f1612b6852.pdf

Giesselmann, J., Meyer, F., & Rohde, C. (2020). A posteriori error analysis and adaptive non-intrusive numerical schemes for systems of random conservation laws. BIT Numer. Math. https://doi.org/10.1007/s10543-019-00794-z

Ginoux, N., Habib, G., Pilca, M., & Semmelmann, U. (2020). An Obata-type characterisation of Calabi metrics on line bundles. North-West. Eur. J. Math., 6, 119--136, i.

Giraud, L., Rüde, U., & Stals, L. (2020). Resiliency in Numerical Algorithm Design for Extreme Scale Simulations (Dagstuhl Seminar 20101). Dagstuhl Reports, 10(3), 1--57. https://doi.org/10.4230/DagRep.10.3.1

Griesemer, M., Hofacker, M., & Linden, U. (2020). From short-range to contact interactions in the 1d Bose gas. Math. Phys. Anal. Geom., 23(2), Paper No. 19, 28. https://doi.org/10.1007/s11040-020-09344-4

Haas, T., de Rijk, B., & Schneider, G. (2020). MODULATION EQUATIONS NEAR THE ECKHAUS BOUNDARY: THE KdV EQUATION. SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 52(6), 5389–5421. https://doi.org/10.1137/19M1266873

Haas, T., & Schneider, G. (2020). Failure of the N-wave interaction approximation without imposing    periodic boundary conditions. ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK, 100(6), Article 6. https://doi.org/10.1002/zamm.201900230

Hilder, B. (2020). Modulating traveling fronts for the Swift-Hohenberg equation in the case of an additional conservation law. Journal of Differential Equations, 269(5), 4353--4380. https://doi.org/10.1016/j.jde.2020.03.033

Hitz, T., Keim, J., Munz, C.-D., & Rohde, C. (2020). A parabolic relaxation model for the Navier-Stokes-Korteweg equations. J. Comput. Phys., 421, 109714. https://doi.org/10.1016/j.jcp.2020.109714

Holicki, T., & Scherer, C. W. (2020). Output-Feedback Synthesis for a Class of Aperiodic Impulsive Systems. IFAC-PapersOnline, 53(2), 7299–7304. https://doi.org/10.1016/j.ifacol.2020.12.981

Holzmüller, D., & Steinwart, I. (2020). Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent. Fakultät für Mathematik und Physik, Universität Stuttgart.

Holzmüller, D., & Steinwart, I. (2020). Training two-layer ReLU networks with gradient descent is inconsistent. arXiv:2002.04861. https://arxiv.org/abs/2002.04861

Jentsch, T., & Weingart, G. (2020). RIEMANNIAN AND KAHLERIAN NORMAL COORDINATES. ASIAN JOURNAL OF MATHEMATICS, 24(3), 369–416.

Kennedy, J. B., & Lang, R. (2020). On the eigenvalues of quantum graph Laplacians with large complex δ couplings. Portugaliae Mathematica. A Journal of the Portuguese Mathematical Society, 77(2), 133–161.

Koch, T., Gläser, D., Weishaupt, K., Ackermann, S., Beck, M., Becker, B., Burbulla, S., Class, H., Coltman, E., Emmert, S., Fetzer, T., Grüninger, C., Heck, K., Hommel, J., Kurz, T., Lipp, M., Mohammadi, F., Scherrer, S., Schneider, M., … Flemisch, B. (2020). 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. https://doi.org/10.1016/j.camwa.2020.02.012

Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2020). 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, 65(1), 109–140. https://doi.org/10.1080/17476933.2019.1631293

Kollross, A. (2020). Octonions, triality, the exceptional Lie algebra F4 and polar actions on the Cayley hyperbolic plane. International Journal of Mathematics, 31(07), 2050051. https://doi.org/10.1142/s0129167x20500512

Magiera, J., Ray, D., Hesthaven, J. S., & Rohde, C. (2020). Constraint-aware neural networks for Riemann problems. J. Comput. Phys., 409(109345), Article 109345. https://doi.org/10.1016/j.jcp.2020.109345

Maier, D. (2020). BREATHER SOLUTIONS ON DISCRETE NECKLACE GRAPHS. OPERATORS AND MATRICES, 14(3), 767–776. https://doi.org/10.7153/oam-2020-14-48

Maier, D. (2020). Construction of breather solutions for nonlinear Klein-Gordon equations    on periodic metric graphs. JOURNAL OF DIFFERENTIAL EQUATIONS, 268(6), 2491–2509. https://doi.org/10.1016/j.jde.2019.09.035

Michalowsky, S., Scherer, C., & Ebenbauer, C. (2020). Robust and structure exploiting optimisation algorithms : an integral quadratic constraint approach. International Journal of Control, 2020, 1–24. https://doi.org/10.1080/00207179.2020.1745286

Minorics, L. A. (2020). Spectral asymptotics for Krein-Feller operators with respect to V-variable Cantor measures. Forum Mathematicum, 32(1), 121–138. https://doi.org/10.1515/forum-2018-0188

Naveira, A. M., & Semmelmann, U. (2020). Conformal Killing forms on nearly Kähler manifolds. Differential Geom. Appl., 70, 101628, 9. https://doi.org/10.1016/j.difgeo.2020.101628

Oesting, M., & Schnurr, A. (2020). Ordinal patterns in clusters of subsequent extremes of regularly varying time series. Extremes, 23(4), 521--545. https://doi.org/10.1007/s10687-020-00391-2

Oladyshkin, S., Mohammadi, F., Kroeker, I., & Nowak, W. (2020). Bayesian(3)Active Learning for the Gaussian Process Emulator Using    Information Theory. ENTROPY, 22(8), Article 8. https://doi.org/10.3390/e22080890

Ostrowski, L., & Rohde, C. (2020). Compressible multicomponent flow in porous media with Maxwell-Stefan diffusion. Math. Meth. Appl. Sci., 43(7), 4200–4221. https://doi.org/10.1002/mma.6185

Ostrowski, L., Massa, F. C., & Rohde, C. (2020). A phase field approach to compressible droplet impingement. In G. Lamanna, S. Tonini, G. E. Cossali, & B. Weigand (Hrsg.), Droplet Interactions and Spray Processes (S. 113–126). Springer International Publishing. https://doi.org/10.1007/978-3-030-33338-6_9

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

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

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. https://doi.org/10.1137/18M1174362

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

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., Mikhailov, S. E., & Wendland, W. L. (2019). 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, 65(1), 109–140. https://doi.org/10.1080/17476933.2019.1631293

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), Article 1, 1850044. 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

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. Phys. Fluids, 31, 012110, Article 31, 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

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., & 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

Gimperlein, H., Meyer, F., Özdemir, C., Stark, D., & Stephan, E. P. (2018). Boundary elements with mesh refinements for the wave equation. Numer. Math., 139(4), 867--912. https://doi.org/10.1007/s00211-018-0954-6

Griesemer, M., & Wünsch, A. (2018). On the domain of the Nelson Hamiltonian. J. Math. Phys., 59(4), 042111, 21. https://doi.org/10.1063/1.5018579

Griesemer, M., & Linden, U. (2018). Stability of the two-dimensional Fermi polaron. Lett. Math. Phys., 108(8), 1837--1849. https://doi.org/10.1007/s11005-018-1055-2

Guo, Y., & Scherer, C. W. (2018). Robust Gain-Scheduled Controller Design with a Hierarchical Structure. IFAC-PapersOnline, 51(25), 228–233. https://doi.org/10.1016/j.ifacol.2018.11.110

Haasdonk, B., Hamzi, B., Santin, G., & Wittwar, D. (2018). Greedy Kernel Methods for Center Manifold Approximation (ArXiv 1810.11329; Nummer 1810.11329).

Haasdonk, B., & Santin, G. (2018). Greedy Kernel Approximation for Sparse Surrogate Modeling. In W. Keiper, A. Milde, & S. Volkwein (Hrsg.), Reduced-Order Modeling (ROM) for Simulation and Optimization: Powerful Algorithms as Key Enablers for Scientific Computing (S. 21--45). Springer International Publishing. https://doi.org/10.1007/978-3-319-75319-5_2

Haesaert, S., Weiland, S., & Scherer, C. W. (2018). A separation theorem for guaranteed $H_2$ performance through matrix inequalities. Automatica, 96, 306–313. https://doi.org/10.1016/j.automatica.2018.07.002

Hang, H., Steinwart, I., Feng, Y., & Suykens, J. A. K. (2018). Kernel Density Estimation for Dynamical Systems. J. Mach. Learn. Res., 19, 1--49.

Harbrecht, H., Wendland, W. L., & Zorii, N. (2018). Minimal energy problems for strongly singular Riesz kernels. Mathematische Nachrichten, 291, 55–85. https://doi.org/10.1002/mana.201600024

Holicki, T., & Scherer, C. W. (2018). A Swapping Lemma for Switched Systems. IFAC-PapersOnLine, 51(25), 346–352. https://doi.org/10.1016/j.ifacol.2018.11.131

Holicki, T., & Scherer, C. W. (2018). Output-Feedback Gain-Scheduling Synthesis for a Class of Switched Systems via Dynamic Resetting $D$-Scalings. 57th IEEE Conf. Decision and Control, 6440–6445. https://doi.org/10.1109/CDC.2018.8619128

Hsiao, G. C., Steinbach, O., & Wendland, W. L. (2018). Boundary Element Methods: Foundation and Error Analysis. Encyclopedia of Computational Mechanics Second Edition, 62. https://doi.org/10.1002/9781119176817.ecm2007

Kohler, M., Krzyzak, A., Tent, R., & Walk, H. (2018). Nonparametric quantile estimation using importance sampling. ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 70(2), 439–465. https://doi.org/10.1007/s10463-016-0595-4

Kohr, M., & Wendland, W. L. (2018). Layer Potentials and Poisson Problems for the Nonsmooth Coefficient Brinkman System in Sobolev and Besov Spaces. Journal of Mathematical Fluid Mechanics, 4(20), 1921–1965. https://doi.org/10.1007/s00021-018-0394-1

Kohr, M., & Wendland, W. L. (2018). Variational approach for the Stokes and Navier–Stokes systems with nonsmooth coefficients in Lipschitz domains on compact Riemannian manifolds. Calculus of Variations and Partial Differential Equations, 57:165, Article 57:165. https://doi.org/10.1007/s00526-018-1426-7

Kovar\’ık, H., Ruszkowski, B., & Weidl, T. (2018). Melas-type bounds for the Heisenberg Laplacian on bounded domains. Journal of Spectral Theory, 8(2), 413--434. https://doi.org/10.4171/jst/200

Kraemer, B., Scharpf, M., Keckstein, S., Dippon, J., Tsaousidis, C., Brunecker, K., Enderle, MD., Neugebauer, A., Nuessle, D., Fend, F., Brucker, S., Taran, FA., Kommoss, S., & Rothmund, R. (2018). A prospective randomized experimental study to investigate the peritoneal adhesion formation after waterjet injection and argon plasma coagulation (HybridAPC) in a rat model. Arch Gynecol Obstet., 2018, Apr;297(4), 961–967. https://doi.org/10.1007/s00404-018-4661-4

Köppel, M., Martin, V., Jaffré, J., & Roberts, J. E. (2018). A Lagrange multiplier method for a discrete fracture model for flow  in porous media. (submitted). https://hal.archives-ouvertes.fr/hal-01700663v2

Köppel, M., Martin, V., & Roberts, J. E. (2018). A stabilized Lagrange multiplier finite-element method for flow in  porous media with fractures. (submitted). https://hal.archives-ouvertes.fr/hal-01761591

Köppl, T., Santin, G., Haasdonk, B., & Helmig, R. (2018). Numerical modelling of a peripheral arterial stenosis using dimensionally  reduced models and kernel methods. International Journal for Numerical Methods in Biomedical Engineering, 0(ja), e3095. https://doi.org/10.1002/cnm.3095

Langer, A. (2018). Investigating the influence of box-constraints on the solution of  a total variation model via an efficient primal-dual method. Journal of Imaging, 4, 1. http://www.mdpi.com/2313-433X/4/1/12

Langer, A. (2018). Locally adaptive total variation for removing mixed Gaussian-impulse  noise. International Journal of Computer Mathematics, 19. https://www.tandfonline.com/doi/abs/10.1080/00207160.2018.1438603

Langer, A. (2018). Overlapping domain decomposition methods for total variation denoising. http://people.ricam.oeaw.ac.at/a.langer/publications/DDfTV.pdf

Maboudi Afkham, B., & Hesthaven, J. S. (2018). Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems. Journal of Scientific Computing, 1–19. https://doi.org/10.1007/s10915-018-0653-6

Magiera, J., & Rohde, C. (2018). A particle-based multiscale solver for compressible liquid-vapor flow. Springer Proc. Math. Stat., 291--304. https://doi.org/10.1007/978-3-319-91548-7_23

Oesting, M., Bel, L., & Lantuéjoul, C. (2018). Sampling from a max-stable process conditional on a homogeneous functional with an application for downscaling climate data. Scand. J. Stat., 45(2), 382--404. https://doi.org/10.1111/sjos.12299

Oesting, M., Schlather, M., & Zhou, C. (2018). Exact and fast simulation of max-stable processes on a compact set using the normalized spectral representation. Bernoulli, 24(2), 1497--1530. https://doi.org/10.3150/16-BEJ905

Oesting, M., & Strokorb, K. (2018). Efficient simulation of Brown-Resnick processes based on variance reduction of Gaussian processes. Adv. in Appl. Probab., 50(4), 1155--1175. https://doi.org/10.1017/apr.2018.54

Oesting, M., & Stein, A. (2018). Spatial modeling of drought events using max-stable processes. Stoch. Env. Res. Risk A., 32(1), 63--81. https://doi.org/10.1007/s00477-017-1406-z

Oesting, M. (2018). Equivalent representations of max-stable processes via $\ell^p$-norms. J. Appl. Probab., 55(1), 54--68. https://doi.org/10.1017/jpr.2018.5

Raja Sekhar, G. P., Sharanya, V., & Rohde, C. (2018). Effect of surfactant concentration and interfacial slip on the flow  past a viscous drop at low surface Péclet number. International Journal of Multiphase Flow, 107, 82–103. http://arxiv.org/abs/1609.03410

Rigaud, G., & Hahn, B. N. (2018). 3D Compton scattering imaging and contour reconstruction for a class of Radon transforms. Inverse Problems, 34(7), 075004. https://doi.org/10.1088/1361-6420/aabf0b

Rohde, C., & Zeiler, C. (2018). On Riemann solvers and kinetic relations for isothermal two-phase  flows with surface tension. Z. Angew. Math. Phys., 3, 69, Art. 76. https://doi.org/10.1007/s00033-018-0958-1

Rohde, C. (2018). Fully resolved compressible two-phase flow : modelling, analytical and numerical issues. In M. Bulicek, E. Feireisl, & M. Pokorný (Hrsg.), New trends and results in mathematical description of fluid flows (S. 115–181). Birkhäuser. https://doi.org/10.1007/978-3-319-94343-5

Ruiz, P. A., Freiberg, U. R., & Kigami, J. (2018). Completely symmetric resistance forms on the stretched Sierpinski gasket. JOURNAL OF FRACTAL GEOMETRY, 5(3), 227–277. https://doi.org/10.4171/JFG/61

Santin, G., Wittwar, D., & Haasdonk, B. (2018). Greedy regularized kernel interpolation (ArXiv preprint 1807.09575; Nummer 1807.09575). University of Stuttgart.

Scherer, C. W., & Veenman, J. (2018). Stability analysis by dynamic dissipation inequalities: On merging frequency-domain techniques with time-domain conditions. Syst. Control Lett., 121, 7–15. https://doi.org/10.1016/j.sysconle.2018.08.005

Scherer, C. W., & Holicki, T. (2018). An IQC theorem for relations: Towards stability analysis of data-integrated systems. IFAC-PapersOnline, 51(25), 390–395. https://doi.org/10.1016/j.ifacol.2018.11.138

Schmidt, A., & Haasdonk, B. (2018). Data-driven surrogates of value functions and applications to feedback control for dynamical systems. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1766

Schmidt, A., Wittwar, D., & Haasdonk, B. (2018). Rigorous and effective a-posteriori error bounds for nonlinear problems -- Application to RB methods [SimTech Preprint]. University of Stuttgart.

Schmidt, A., & Haasdonk, B. (2018). Reduced basis approximation of large scale parametric algebraic Riccati equations. ESAIM: Control, Optimisation and Calculus of Variations, 24(1), 129--151. https://doi.org/10.1051/cocv/2017011

Seus, D., Pop, I. S., Rohde, C., Mitra, K., & Radu, F. (2018). A linear domain decompostition method for partially saturated flow in porous media. Comput. Methods Appl. Mech. Eng., 333, 331–355. https://doi.org/10.1016/j.cma.2018.01.029

Seus, D., Mitra, K., Pop, I. S., Radu, F. A., & Rohde, C. (2018). A linear domain decomposition method for partially saturated flow  in porous media. Comp. Methods Appl. Mech. Eng., 333, 331--355. https://doi.org/10.1016/j.cma.2018.01.029

Sharanya, V., Sekhar, G. P. R., & Rohde, C. (2018). The low surface Péclet number regime for surfactant-laden viscous droplets: Influence of surfactant concentration, interfacial slip effects and cross migration. Int. J. of Multiph. Flow, 107, 82–103. https://doi.org/10.1016/j.ijmultiphaseflow.2018.05.008

Wittwar, D., Santin, G., & Haasdonk, B. (2018). Interpolation with uncoupled separable matrix-valued kernels. ArXiv e-prints.

Wittwar, D., & Haasdonk, B. (2018). Greedy Algorithms for Matrix-Valued Kernels. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1773

Zhang, R., Kyriss, T., Dippon, J., Hansen, M., Boedeker, E., & Friedel, G. (2018). American Society of Anesthesiologists physical status facilitates risk stratification of elderly patients undergoing thoracoscopic lobectomy. European Journal of Cardio-Thoracic Surgery, 53(5), 973–979. https://doi.org/10.1093/ejcts/ezx436

Zhang, R., Kyriss, T., Dippon, J., Ciupa, S., Boedeker, E., & Friedel, G. (2018). Impact of comorbidity burden on morbidity following horacoscopic lobectomy: a propensity-matched analysis. J Thorac Dis., 2018 Mar;10(3), 1806–1814. https://doi.org/10.21037/jtd.2018.02.62

Alkämper, M., & Klöfkorn, R. (2017). Distributed Newest Vertex Bisection. Journal of Parallel and Distributed Computing, 104, 1–11. http://dx.doi.org/10.1016/j.jpdc.2016.12.003

Alkämper, M., Klöfkorn, R., & Gaspoz, F. (2017). A Weak Compatibility Condition for Newest Vertex Bisection in any  Dimension. http://arxiv.org/abs/1711.03141

Alkämper, M., & Langer, A. (2017). Using DUNE-ACFem for Non-smooth Minimization of Bounded Variation  Functions. Archive of Numerical Software, 5(1), 3--19. https://journals.ub.uni-heidelberg.de/index.php/ans/article/view/27475

Alla, A., Haasdonk, B., & Schmidt, A. (2017). Feedback control of parametrized PDEs via model order reduction and dynamic programming principle. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1765

Alla, A., Gunzburger, M., Haasdonk, B., & Schmidt, A. (2017). Model order reduction for the control of parametrized partial differential equations via dynamic programming principle. University of Stuttgart.

Alla, A., Schmidt, A., & Haasdonk, B. (2017). Model Order Reduction Approaches for Infinite Horizon Optimal Control  Problems via the HJB Equation. In P. Benner, M. Ohlberger, A. Patera, G. Rozza, & K. Urban (Hrsg.), Model Reduction of Parametrized Systems (S. 333--347). Springer International Publishing. https://doi.org/10.1007/978-3-319-58786-8_21

Barth, A., & Fuchs, F. G. (2017). Uncertainty quantification for linear hyperbolic equations with    stochastic process or random field coefficients. APPLIED NUMERICAL MATHEMATICS, 121, 38–51. https://doi.org/10.1016/j.apnum.2017.06.009

Barth, A., Harrach, B., Hyvoenen, N., & Mustonen, L. (2017). Detecting stochastic inclusions in electrical impedance tomography. INVERSE PROBLEMS, 33(11), Article 11. https://doi.org/10.1088/1361-6420/aa8f5c

Barth, A., & Stein, A. (2017). A study of elliptic partial differential equations with jump diffusion  coefficients.

Barth, A., Harrach, B., Hyvönen, N., & Mustonen, L. (2017). Detecting stochastic inclusions in electrical impedance tomography. Inv. Prob., 33(11), 115012. http://arxiv.org/abs/1706.03962

Baur, U., Benner, P., Haasdonk, B., Himpe, C., Maier, I., & Ohlberger, M. (2017). Comparison of methods for parametric model order reduction of instationary problems. In P. Benner, A. Cohen, M. Ohlberger, & K. Willcox (Hrsg.), Model Reduction and Approximation: Theory and Algorithms. SIAM Philadelphia. https://www2.mpi-magdeburg.mpg.de/preprints/2015/MPIMD15-01.pdf

Bhatt, A., & VanGorder, R. (2017). Chaos in a non-autonomous nonlinear system describing asymmetric  water wheels.

Brehler, M., Schirwon, M., Göddeke, D., & Krummrich, P. M. (2017). A GPU-Accelerated Fourth-Order Runge-Kutta in the Interaction Picture Method for the Simulation of Nonlinear Signal Propagation in Multimode Fibers. Journal of Lightwave Technology, 35(17), 3622–3628. https://doi.org/10.1109/JLT.2017.2715358

Brünnette, T., Santin, G., & Haasdonk, B. (2017). Greedy kernel methods for accelerating implicit integrators for parametric ODEs. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1767

Bürger, R., & Kröker, I. (2017). Hybrid Stochastic Galerkin Finite Volumes for the Diffusively Corrected  Lighthill-Whitham-Richards Traffic Model. In C. Cancès & P. Omnes (Hrsg.), Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic  and Parabolic Problems: FVCA 8, Lille, France, June 2017 (S. 189--197). Springer International Publishing. https://doi.org/10.1007/978-3-319-57394-6_21

Cavoretto, R., De Marchi, S., De Rossi, A., Perracchione, E., & Santin, G. (2017). Partition of unity interpolation using stable kernel-based techniques. APPLIED NUMERICAL MATHEMATICS, 116(SI), 95–107. https://doi.org/10.1016/j.apnum.2016.07.005

Chalons, C., Rohde, C., & Wiebe, M. (2017). A finite volume method for undercompressive shock waves in two space dimensions. ESAIM Math. Model. Numer. Anal., 51(5), 1987–2015. https://doi.org/10.1051/m2an/2017027

Chertock, A., Degond, P., & Neusser, J. (2017). An asymptotic-preserving method for a relaxation of the    Navier-Stokes-Korteweg equations. JOURNAL OF COMPUTATIONAL PHYSICS, 335, 387–403. https://doi.org/10.1016/j.jcp.2017.01.030

De Marchi, S., Iske, A., & Santin, G. (2017). Image Reconstruction from Scattered Radon Data by Weighted Positive  Definite Kernel Functions.

De Marchi, S., Idda, A., & Santin, G. (2017). A Rescaled Method for RBF Approximation. In G. E. Fasshauer & L. L. Schumaker (Hrsg.), Approximation Theory XV: San Antonio 2016 (S. 39--59). Springer International Publishing. https://doi.org/10.1007/978-3-319-59912-0_3

Diaz Ramos, J. C., Dominguez Vazquez, M., & Kollross, A. (2017). Polar actions on complex hyperbolic spaces. Mathematische Zeitschrift, 287(3), 1183--1213. https://doi.org/10.1007/s00209-017-1864-5

Dibak, C., Schmidt, A., Dürr, F., Haasdonk, B., & Rothermel, K. (2017). Server-assisted interactive mobile simulations for pervasive applications. 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom), 111--120. https://doi.org/10.1109/PERCOM.2017.7917857

Dombry, C., Engelke, S., & Oesting, M. (2017). Bayesian inference for multivariate extreme value distributions. Electron. J. Stat., 11(2), 4813--4844. https://doi.org/10.1214/17-EJS1367

Farooq, M., & Steinwart, I. (2017). An SVM-like Approach for Expectile Regression. Comput. Statist. Data Anal., 109, 159--181. https://doi.org/10.1016/j.csda.2016.11.010

Fechter, S., Munz, C.-D., Rohde, C., & Zeiler, C. (2017). A sharp interface method for compressible liquid-vapor flow with phase transition and surface tension. J. Comput. Phys., 336, 347–374. https://doi.org/10.1016/j.jcp.2017.02.001

Fehr, J., Grunert, D., Bhatt, A., & Hassdonk, B. (2017). A Sensitivity Study of Error Estimation in Reduced Elastic Multibody  Systems. Proceedings of MATHMOD 2018, Vienna, Austria.

Feistauer, M., Roskovec, F., & Sändig, A.-M. (2017). Discontinuous Galerkin Method for an Elliptic Problem with Nonlinear  Boundary Conditions in a Polygon. IMA, 00, 1–31. https://doi.org/10.1093/imanum/drx070

Feistauer, M., Bartos, O., Roskovec, F., & Sändig, A.-M. (2017). Analysis of the FEM and DGM for an elliptic problem with a nonlinear  Newton boundary condition. Proceeding of the EQUADIFF 17, 127–136. http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/equadiff/

Fetzer, M., & Scherer, C. W. (2017). Absolute stability analysis of discrete time feedback interconnections. IFAC-PapersOnLine, 1, Article 1. https://doi.org/10.1016/j.ifacol.2017.08.757

Fetzer, M., & Scherer, C. W. (2017). Full‐block multipliers for repeated, slope‐restricted scalar nonlinearities. Int. J. Robust Nonlin., 27(17), 3376–3411. https://doi.org/10.1002/rnc.3751

Fetzer, M., & Scherer, C. W. (2017). Zames-Falb Multipliers for Invariance. IEEE Control Systems Letters, 1(2), 412–417. https://doi.org/10.1109/LCSYS.2017.2718556

Fetzer, M., Scherer, C. W., & Veenman, J. (2017). Invariance with dynamic multipliers. IEEE Trans. Autom. Control, 63(7), 1929–1942. https://doi.org/10.1109/TAC.2017.2762764

Fetzer, M. (2017). From classical absolute stability tests towards a comprehensive robustness analysis [Dissertation, University of Stuttgart]. https://doi.org/10.18419/opus-9726

Fukuizumi, R., Marzuola, J. L., Pelinovsky, D., & Schneider, G. (Hrsg.). (2017). Nonlinear partial differential equations on graphs. Abstracts from the workshop held June 18--24, 2017. Oberwolfach Rep., 14(2), 1805--1868.

Funke, S., Mendel, T., Miller, A., Storandt, S., & Wiebe, M. (2017). Map Simplification with Topology Constraints: Exactly and in Practice. Proceedings of the Ninteenth Workshop on Algorithm Engineering and  Experiments, ALENEX 2017, Barcelona, Spain, Hotel Porta Fira, January  17-18, 2017., 185--196. https://doi.org/10.1137/1.9781611974768.15

Gaspoz, F. D., Kreuzer, C., Siebert, K., & Ziegler, D. (2017). A convergent time-space adaptive $dG(s)$ finite element method for  parabolic problems motivated by equal error distribution. In Submitted. https://arxiv.org/abs/1610.06814

Gaspoz, F. D., Morin, P., & Veeser, A. (2017). A posteriori error estimates with point sources in fractional sobolev spaces. NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS, 33(4), 1018–1042. https://doi.org/10.1002/num.22065

Geck, M. (2017). On the construction of semisimple Lie algebras and Chevalley groups. Proceedings of the American Mathematical Society, 145(8), 3233--3247. https://doi.org/10.1090/proc/13600

Geck, M., & Müller, J. (2017). Invariant bilinear forms on W-graph representations and linear algebra over integral domains. Algorithmic and experimental methods in algebra, geometry and number theory (eds. G. Böckle, W. Decker, G. Malle), 311–360. https://doi.org/10.1007/978-3-319-70566-8_13

Geck, M. (2017). Minuscule weights and Chevalley                      groups. Finite Simple Groups: Thirty Years of the Atlas and Beyond (Celebrating the Atlases and Honoring John Conway, November 2-5, 2015 at Princeton University), 694, 159--176. https://doi.org/10.1090/conm/694/13955

Geck, M. (2017). James’ Submodule Theorem and the Steinberg Module. Symmetry, Integrability and Geometry: Methods and Applications, 13. https://doi.org/10.3842/sigma.2017.091

Geck, M. (2017). On the modular composition factors of the Steinberg representation. Journal of Algebra, 475, 370--391. https://doi.org/10.1016/j.jalgebra.2015.11.005

Giesselmann, J., & Pryer, T. (2017). Goal-oriented error analysis of a DG scheme for a second gradient  elastodynamics model. In C. Cances & P. Omnes (Hrsg.), Finite Volumes for Complex Applications VIII-Methods and Theoretical  Aspects (Bd. 199). http://www.springer.com/de/book/9783319573960

Giesselmann, J., & Tzavaras, A. E. (2017). Stability properties of the Euler-Korteweg system with nonmonotone  pressures. Appl. Anal., 96(9), 1528–1546. https://doi.org/10.1080/00036811.2016.1276175

Giesselmann, J., & Pryer, T. (2017). A posteriori analysis for dynamic model adaptation in convection-dominated problems. MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES, 27(13), 2381–2423. https://doi.org/10.1142/S0218202517500476

Giesselmann, J., Lattanzio, C., & Tzavaras, A. E. (2017). Relative Energy for the Korteweg Theory and Related Hamiltonian Flows in Gas Dynamics. ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS, 223(3), 1427–1484. https://doi.org/10.1007/s00205-016-1063-2

Griesemer, M., Schmid, J., & Schneider, G. (2017). On the dynamics of the mean-field polaron in the              high-frequency limit. Lett. Math. Phys., 107(10), 1809--1821. https://doi.org/10.1007/s11005-017-0969-4

Griesemer, M. (2017). On the dynamics of polarons in the strong-coupling limit. Rev. Math. Phys., 29(10), 1750030, 21. https://doi.org/10.1142/S0129055X17500301

Gutt, R., Kohr, M., Mikhailov, S., & Wendland, W. L. (2017). On the mixed problem for the semilinear Darcy-Forchheimer-Brinkman  systems in Besov spaces on creased Lipschitz domains. Math. Meth. Appl. Sci., 18, 7780–7829. https://doi.org/10.1002/mma.4562

Gutt, R., Kohr, M., Mikhailov, S. E., & Wendland, W. L. (2017). On the mixed problem for the semilinear Darcy-Forchheimer-Brinkman PDE system in Besov spaces on creased Lipschitz domains. MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 40(18), 7780–7829. https://doi.org/10.1002/mma.4562

Haasdonk, B. (2017). Reduced Basis Methods for Parametrized PDEs -- A Tutorial Introduction for Stationary and Instationary Problems. In P. Benner, A. Cohen, M. Ohlberger, & K. Willcox (Hrsg.), Model Reduction and Approximation: Theory and Algorithms (S. 65--136). SIAM, Philadelphia. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=938

Hahn, B. N. (2017). A motion artefact study and locally deforming objects in computerized tomography. Inverse Problems, 33(11), 114001. https://doi.org/10.1088/1361-6420/aa8d7b

Hahn, B. N. (2017). Motion Estimation and Compensation Strategies in Dynamic Computerized Tomography. Sensing and Imaging, 18(10), 1–20. https://doi.org/10.1007/s11220-017-0159-6

Hang, H., & Steinwart, I. (2017). A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning. Ann. Statist., 45, 708--743. https://doi.org/10.1214/16-AOS1465

Harbrecht, H., Wendland, W. L., & Zorii, N. (2017). Riesz energy problems for strongly singular kernels. Math. Nachr. https://doi.org/10.1002/mana.201600024

Heil, K., Moroianu, A., & Semmelmann, U. (2017). Killing tensors on tori. J. Geom. Phys., 117, 1--6. https://doi.org/10.1016/j.geomphys.2017.02.010

Hintermüller, M., Rautenberg, C. N., Wu, T., & Langer, A. (2017). Optimal Selection of the Regularization Function in a Weighted Total  Variation Model. Part II: Algorithm, Its Analysis and Numerical Tests. Journal of Mathematical Imaging and Vision, 1--19. https://link.springer.com/article/10.1007/s10851-017-0736-2

Hintermüller, M., Langer, A., Rautenberg, C. N., & Wu, T. (2017). Adaptive regularization for reconstruction from subsampled data. WIAS Preprint No. 2379. http://www.wias-berlin.de/preprint/2379/wias_preprints_2379.pdf

Hänel, A., & Weidl, T. (2017). Spectral asymptotics for the Dirichlet Laplacian with a Neumann window via a Birman-Schwinger analysis of the Dirichlet-to-Neumann operator. Functional Analysis and Operator Theory for Quantum Physics, EMS Series of Congress Reports, J. Dittrich, et al. (Eds.), 315–352.

Höllig, K. V., & Hörner, J. V. (Hrsg.). (2017). Aufgaben und Lösungen zur höheren Mathematik (S. xi, 533 Seiten) [Aufgabensammlung]. Springer Spektrum. http://deposit.d-nb.de/cgi-bin/dokserv?id=86f385b1e03e40a0a23a214a0c3c5f72&prov=M&dok_var=1&dok_ext=htm

Kane, B., Klöfkorn, R., & Gersbacher, C. (2017). hp--Adaptive Discontinuous Galerkin Methods for Porous Media Flow. International Conference on Finite Volumes for Complex Applications, 447--456.

Kane, B. (2017). Using DUNE-FEM for Adaptive Higher Order Discontinuous Galerkin  Methods for Two-phase Flow in Porous Media. Archive of Numerical Software, 5(1), 129--149.

Kohr, M., Medkova, D., & Wendland, W. L. (2017). On the Oseen-Brinkman flow around an (m-1)-dimensional obstacle. Monatshefte für Mathematik, 483, 269–302. https://doi.org/MOFM-D16-00078

Kohr, M., Mikhailov, S., & Wendland, W. L. (2017). Transmission problems for the Navier-Stokes and Darcy-Forchheimer-Brinkman  systems in Lipschitz domains on compact Riemannian mani. J of Mathematical Fluid Mechanics, 19, 203–238.

Kollross, A. (2017). Hyperpolar actions on reducible symmetric spaces. Transformation Groups, 22(1), 207--228. https://doi.org/10.1007/s00031-016-9384-7

Kovarik, H., Ruszkowski, B., & Weidl, T. (2017). Spectral estimates for the Heisenberg Laplacian on cylinders. Functional Analysis and Operator Theory for Quantum Physics, EMS Series of Congress Reports, J. Dittrich, et al. (eds.), 433–446.

Kutter, M., Rohde, C., & Sändig, A.-M. (2017). Well-posedness of a two scale model for liquid phase epitaxy with elasticity. Contin. Mech. Thermodyn., 29(4), 989–1016. https://doi.org/10.1007/s00161-015-0462-1

Köppel, M., Franzelin, F., Kröker, I., Oladyshkin, S., Santin, G., Wittwar, D., Barth, A., Haasdonk, B., Nowak, W., Pflüger, D., & Rohde, C. (2017). Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1759

Köppel, M., Kröker, I., & Rohde, C. (2017). Intrusive Uncertainty Quantification for Hyperbolic-Elliptic Systems  Governing Two-Phase Flow in Heterogeneous Porous Media. Comput. Geosci., 21, 807–832. https://doi.org/10.1007/s10596-017-9662-z

Köppel, M., Franzelin, F., Kröker, I., Oladyshkin, S., Wittwar, D., Santin, G., Barth, A., Haasdonk, B., Nowak, W., Pflüger, D., & Rohde, C. (2017). Datasets and executables of data-driven uncertainty quantification benchmark in carbon dioxide storage. https://doi.org/10.5281/zenodo.933827

Köppl, T., Santin, G., Haasdonk, B., & Helmig, R. (2017). Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods. University of Stuttgart.

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

Langer, A. (2017). Automated Parameter Selection for Total Variation Minimization in  Image Restoration. Journal of Mathematical Imaging and Vision, 57, 239--268. https://doi.org/10.1007/s10851-016-0676-2

Maboudi Afkham, B., & Hesthaven, J. (2017). Structure Preserving Model Reduction of Parametric Hamiltonian Systems. SIAM Journal on Scientific Computing, 39(6), A2616–A2644. https://doi.org/10.1137/17M1111991

Martini, I., Rozza, G., & Haasdonk, B. (2017). Certified Reduced Basis Approximation for the Coupling of Viscous  and Inviscid Parametrized Flow Models. Journal of Scientific Computing. https://doi.org/10.1007/s10915-017-0430-y

Maz’ya, V., Natroshvili, D., Shargorodsky, E., & Wendland, W. L. (Hrsg.). (2017). Recent Trends in Operator Theory and Partial Differential Equations.  The Roland Duduchava Anniverary Volume (Nr. 258; Nummer 258). Birkhäuser/Springer International.

Minbashian, H., Adibi, H., & Dehghan, M. (2017). On Resolution of Boundary Layers of Exponential Profile with Small  Thickness Using an Upwind Method in IGA.

Minbashian, H. (2017). Wavelet-based Multiscale Methods for Numerical Solution of Hyperbolic  Conservation Laws. Amirkabir University of Technology (Tehran 11/2017 Polytechnic),  Tehran, Iran.

Minbashian, H., Adibi, H., & Dehghan, M. (2017). An adaptive wavelet space-time SUPG method for hyperbolic conservation  laws. Numerical Methods for Partial Differential Equations, 33(6), 2062–2089. https://doi.org/10.1002/num.22180

Minbashian, H., Adibi, H., & Dehghan, M. (2017). An Adaptive Space-Time Shock Capturing Method with High Order Wavelet  Bases for the System of Shallow Water Equations. International Journal of Numerical Methods for Heat & Fluid Flow.

Oesting, M., Schlather, M., & Friederichs, P. (2017). Statistical post-processing of forecasts for extremes using bivariate Brown-Resnick processes with an application to wind gusts. Extremes, 20(2), 309--332. https://doi.org/10.1007/s10687-016-0277-x

Pelinovsky, D., & Schneider, G. (2017). Bifurcations of standing localized waves on periodic graphs. Ann. Henri Poincaré, 18(4), 1185--1211.

Rösinger, C. A., & Scherer, C. W. (2017). Structured Controller Design With Applications to Networked Systems. Proc. 56th IEEE Conf. Decision and Control. https://doi.org/10.1109/CDC.2017.8264365

Santin, G., & Haasdonk, B. (2017). Convergence rate of the data-independent P-greedy algorithm in kernel-based approximation. Dolomites Res. Notes Approx., 10, 68--78. /brokenurl#www.emis.de/journals/DRNA/9-2.html

Santin, G., & Haasdonk, B. (2017). Greedy Kernel Approximation for Sparse Surrogate Modelling. University of Stuttgart.

Santin, G., & Haasdonk, B. (2017). Non-symmetric kernel greedy interpolation.

Schanz, M., Schaaf, L., Dippon, J., Biegger, D., Fritz, P., Alscher, MD., & Kimmel, M. (2017). Renal effects of metallothionein induction by zinc in vitro and in vivo. BMC Nephrol, 2017 Mar 16;18(1), 91. https://doi.org/10.1186/s12882-017-0503-z

Schanz, M., Ketteler, M., Heck, M., Dippon, J., Alscher, MD., & Kimmel, M. (2017). Impact of an in-Hospital Patient Education Program on Choice of Renal Replacement Modality in Unplanned Dialysis Initiation. Kidney & blood pressure research, 42(5), 865–876. https://doi.org/10.1159/000484531

Schmid, J., & Griesemer, M. (2017). Well-posedness of non-autonomous linear evolution equations in              uniformly convex spaces. Math. Nachr., 290(2–3), 435--441. https://doi.org/10.1002/mana.201500052

Schmidt, A., & Haasdonk, B. (2017). Data-driven surrogates of value functions and applications to feedback  control for dynamical systems. University of Stuttgart. http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1742

Schmidt, A., & Haasdonk, B. (2017). Reduced basis approximation of large scale parametric algebraic Riccati  equations. ESAIM: Control, Optimisation and Calculus of Variations. https://doi.org/10.1051/cocv/2017011

Schneider, G., & Uecker, H. (2017). Nonlinear PDEs. A dynamical systems approach. In Grad. Stud. Math. (Bd. 182, S. xiii + 575). Providence, RI: American Mathematical Society (AMS).

Steinwart, I. (2017). A Short Note on the Comparison of Interpolation Widths, Entropy Numbers, and Kolmogorov Widths. J. Approx. Theory, 215, 13--27. https://doi.org/10.1016/j.jat.2016.11.006

Steinwart, I., & Thomann, P. (2017). liquidSVM: A Fast and Versatile SVM Package. Fakultät für Mathematik und Physik, Universität Stuttgart.

Steinwart, I., Sriperumbudur, B. K., & Thomann, P. (2017). Adaptive Clustering Using Kernel Density Estimators. Fakultät für Mathematik und Physik, Universität Stuttgart.

Steinwart, I. (2017). A Short Note on the Comparison of Interpolation Widths, Wntropy Numbers, and Kolmogorov Widths. J. Approx. Theory, 215, 13--27.

Steinwart, I. (2017). Representation of Quasi-Monotone Functionals by Families of Separating Hyperplanes. Math. Nachr., 290, 1859--1883. https://doi.org/10.1002/mana.201500350

Tempel, P., Schmidt, A., Haasdonk, B., & Pott, A. (2017). Application of the Rigid Finite Element Method to the Simulation  of Cable-Driven Parallel Robots. In Computational Kinematics (S. 198--205). Springer International Publishing. https://doi.org/10.1007/978-3-319-60867-9_23

Thomann, P., Steinwart, I., Blaschzyk, I., & Meister, M. (2017). Spatial Decompositions for Large Scale SVMs. In A. Singh & J. Zhu (Hrsg.), Proceedings of Machine Learning Research Volume 54: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics 2017 (S. 1329--1337).

Wirth, J. (2017). On t-dependent hyperbolic systems. Part 2. J. Math. Anal. Appl., 448(1), 293--318. https://doi.org/10.1016/j.jmaa.2016.11.026

Wirth, J. (2017). Regular singular problems for hyperbolic systems and their              asymptotic integration. In New trends in analysis and interdisciplinary applications (S. 553--561). Birkhäuser/Springer, Cham. https://doi.org/10.1007/978-3-319-48812-7_70

Wittwar, D., Santin, G., & Haasdonk, B. (2017). Interpolation with uncoupled separable matrix-valued kernels. [ArXiv preprint 1807.09111, Accepted for publications in Dolomites Res. Notes Approx.].

Wittwar, D., & Haasdonk, B. (2017). On uncoupled separable matrix-valued kernels. University of Stuttgart.

Wittwar, D., Schmidt, A., & Haasdonk, B. (2017). Reduced Basis Approximation for the Discrete-time Parametric Algebraic  Riccati Equation. University of Stuttgart.