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.
2025
- Barth, A., & Stein, A. (2025). A stochastic transport problem with Lévy noise: Fully discrete numerical approximation. Mathematics and Computers in Simulation, 227, 347–370. https://doi.org/10.1016/j.matcom.2024.07.036
2024
- "Knobloch, P., "Kuzmin, D., & "Jha, A. (2024). Well-balanced convex limiting for finite element discretizations of steady convection-diffusion-reaction equations (P. "Knobloch, D. "Kuzmin, & A. "Jha, Hrsg.).
- Albişoru, A. F., Kohr, M., Papuc, I., & Wendland, W. L. (2024). On some Robin–transmission problems for the Brinkman system and a Navier–Stokes type system. Math. Meth. Appl. Sci., 1–28. https://doi.org/10.1002/mma.10170
- Alkämper, M., Magiera, J., & Rohde, C. (2024). An Interface-Preserving Moving Mesh in Multiple Space Dimensions. ACM Trans. Math. Softw., 50(1), Article 1. https://doi.org/10.1145/3630000
- Beschle, C., & Barth, A. (2024). Complexity analysis of quasi continuous level Monte Carlo. ESAIM: Mathematical Modelling and Numerical Analysis. https://doi.org/10.1051/m2an/2024039
- Beschle, C. A., & Barth, A. (2024). Quasi continuous level Monte Carlo for random elliptic PDEs. In Hinrichs, A., Kritzer, P., Pillichshammer, F. (eds) Monte Carlo and Quasi-Monte Carlo Methods. MCQMC 2022 (Bd. 460, S. 3–31). Springer Proceedings in Mathematics & Statistics. https://doi.org/10.1007/978-3-031-59762-6_1
- Bondanza, M., Nottoli, T., Nottoli, M., Cupellini, L., Lipparini, F., & Mennucci, B. (2024). The OpenMMPol library for polarizable QM/MM calculations of properties and dynamics. The Journal of Chemical Physics, 160(13), Article 13. https://doi.org/10.1063/5.0198251
- Braun, A., Kohler, M., Langer, S., & Walk, H. (2024). Convergence rates for shallow neural networks learned by gradient descent. Bernoulli, 30(1), Article 1. https://doi.org/10.3150/23-bej1605
- Buchfink, P., Glas, S., Haasdonk, B., & Unger, B. (2024). Model reduction on manifolds: A differential geometric framework (2024 Physica D, Hrsg.). https://arxiv.org/abs/2312.01963
- Claeys, X., Hassan, M., & Stamm, B. (2024). Continuity estimates for Riesz potentials on polygonal boundaries. Partial Differential Equations and Applications. https://doi.org/10.1007/s42985-024-00280-4
- Corso, T. C., Hassan, M., Jha, A., & Stamm, B. (2024). An $L^2$-maximum principle for circular arcs on the disk.
- Döppel, F., Wenzel, T., Herkert, R., Haasdonk, B., & Votsmeier, M. (2024). Goal‐Oriented Two‐Layered Kernel Models as Automated Surrogates for Surface Kinetics in Reactor Simulations. Chemie Ingenieur Technik, 96(6), Article 6. https://doi.org/10.1002/cite.202300178
- Ghosh, T., Bringedal, C., Rohde, C., & Helmig, R. (2024). A phase-field approach to model evaporation from porous media: Modeling and upscaling. https://arxiv.org/abs/2112.13104
- Giannoulis, I., Schmidt, B., & Schneider, G. (2024). NLS approximation for a scalar FPUT system on a 2D square lattice with a cubic nonlinearity. J. Math. Anal. Appl., 540(2), Article 2. https://doi.org/10.1016/j.jmaa.2024.128625
- Hammer, M., Wenzel, T., Santin, G., Meszaros-Beller, L., Little, J. P., Haasdonk, B., & Schmitt, S. (2024). A new method to design energy-conserving surrogate models for the coupled, nonlinear responses of intervertebral discs. Biomechanics and Modeling in Mechanobiology, 23(3), Article 3. https://doi.org/10.1007/s10237-023-01804-4
- Herkert, R., Buchfink, P., Wenzel, T., Haasdonk, B., Toktaliev, P., & Iliev, O. (2024). Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data. Mathematics, 12(13), Article 13. https://doi.org/10.3390/math12132111
- Herkert, R. R. (2024). Replication Code for: Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data. https://doi.org/10.18419/darus-4227
- Homs-Pons, C., Lautenschlager, R., Schmid, L., Ernst, J., Göddeke, D., Röhrle, O., & Schulte, M. (2024). Coupled Simulation and Parameter Inversion for Neural System and Electrophysiological Muscle Models. GAMM-Mitteilungen. https://doi.org/10.1002/gamm.202370009
- Hsiao, G. C., Sánchez-Vizuet, T., & Wendland, W. L. (2024). Boundary-field formulation for transient electromagnetic scattering by dielectric scatterers and coated conductors. In SIAM J. Math. Analysis, to appear. https://doi.org/10.48550/arXiv.2406.05367
- Huber, F., Bürkner, P.-C., Göddeke, D., & Schulte, M. (2024). Knowledge-based modeling of simulation behavior for Bayesian optimization. Computational Mechanics, 74(1), Article 1. https://doi.org/10.1007/s00466-023-02427-3
- Huber, F., Bürkner, P.-C., Göddeke, D., & Schulte, M. (2024). Knowledge-based modeling of simulation behavior for Bayesian optimization. Computational Mechanics. https://doi.org/10.1007/s00466-023-02427-3
- Hörl, M., & Rohde, C. (2024). Rigorous Derivation of Discrete Fracture Models for Darcy Flow in the Limit of Vanishing Aperture. Netw. Heterog. Media, 19(1), Article 1. https://doi.org/10.3934/nhm.2024006
- Jha, A. (2024). Residual-Based a Posteriori Error Estimators for Algebraic Stabilizations. Applied Mathematics Letters, 157, 109192. https://doi.org/10.1016/j.aml.2024.109192
- Karabash, I. M., Lienstromberg, C., & Velázquez, J. J. L. (2024). Multi-parameter Hopf bifurcations of rimming flows. https://doi.org/10.48550/arXiv.2406.11690
- Kharitenko, A., & Scherer, C. W. (2024). On the exactness of a stability test for Lur’e systems with slope-restricted nonlinearities. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2024.3362859
- Kohr, M., Nistor, V., & Wendland, W. L. (2024). The Stokes operator on manifolds with cylindrical ends. Journal of Differential Equations, 407, Article 407. https://doi.org/10.1016/j.jde.2024.06.017
- Lindgren, E. B., Avis, H., Miller, A., Stamm, B., Besley, E., & Stace, A. J. (2024). The significance of multipole interactions for the stability of regular structures composed from charged particles. Journal of Colloid and Interface Science, 663, 458–466. https://doi.org/10.1016/j.jcis.2024.02.146
- Lukácová-Medvid’ová, M., & Rohde, C. (2024). Mathematical Challenges for the Theory of Hyperbolic Balance Laws in Fluid Mechanics: Complexity, Scales, Randomness. In Accepted for publication in Jahresber. Dtsch. Math.-Ver.
- Lukácová-Medvid’ová, M., & Rohde, C. (2024). Mathematical Challenges for the Theory of Hyperbolic Balance Laws in Fluid Mechanics: Complexity, Scales, Randomness.
- Magiera, J., & Rohde, C. (2024). A Multiscale Method for Two-Component, Two-Phase Flow with a Neural Network Surrogate. Communications on Applied Mathematics and Computation. https://doi.org/10.1007/s42967-023-00349-8
- Maier, B., Göddeke, D., Huber, F., Klotz, T., Röhrle, O., & Schulte, M. (2024). OpenDiHu: An Efficient and Scalable Framework for Biophysical Simulations of the Neuromuscular System. Journal of Computational Science, 79(102291), Article 102291. https://doi.org/10.1016/j.jocs.2024.102291
- Maier, B., Göddeke, D., Huber, F., Klotz, T., Röhrle, O., & Schulte, M. (2024). OpenDiHu: An Efficient and Scalable Framework for Biophysical Simulations of the Neuromuscular System. Journal of Computational Science, 79. https://doi.org/10.1016/j.jocs.2024.102291
- Meijer, T. J., Holicki, T., Eijnden, S. J. A. M. van den, Scherer, C. W., & Heemels, W. P. M. H. (2024). The Non-Strict Projection Lemma. IEEE Transactions on Automatic Control, 1–8. https://doi.org/10.1109/TAC.2024.3371374
- Mel’nyk, T. A., & Durante, T. (2024). Spectral problems with perturbed Steklov conditions in thick junctions with branched structure. Applicable Analysis, 1–26. https://doi.org/10.1080/00036811.2024.2322644
- Mel’nyk, T., & Rohde, C. (2024). Asymptotic expansion for convection-dominated transport in a thin graph-like junction. Analysis and Applications, 22 (05), 833–879. https://doi.org/10.1142/S0219530524500040
- Mel’nyk, T., & Rohde, C. (2024). Asymptotic approximations for semilinear parabolic convection-dominated transport problems in thin graph-like networks. J. Math. Anal. Appl., 529(1), Article 1. https://doi.org/10.1016/j.jmaa.2023.127587
- Mel’nyk, T., & Rohde, C. (2024). Reduced-dimensional modelling for nonlinear convection-dominated flow in cylindric domains. Nonlinear Differ. Equ. Appl., 31:105. https://doi.org/10.1007/s00030-024-00997-6
- Mel’nyk, T., & Rohde, C. (2024). Puiseux asymptotic expansions for convection-dominated transport problems in thin graph-like networks: strong boundary interactions. Asymptotic Analysis, 137, 27–52. https://doi.org/10.3233/ASY-231876
- Miao, Y., Rohde, C., & Tang, H. (2024). Well-posedness for a stochastic Camassa-Holm type equation with higher order nonlinearities. Stoch. Partial Differ. Equ. Anal. Comput., 12(1), Article 1. https://doi.org/10.1007/s40072-023-00291-z
- Nottoli, M., Herbst, M. F., Mikhalev, A., Jha, A., Lipparini, F., & Stamm, B. (2024). ddX: Polarizable continuum solvation from small molecules to proteins. WIREs Computational Molecular Science. https://doi.org/10.1002/wcms.1726
- Nottoli, M., Vanich, E., Cupellini, L., Scalmani, G., Pelosi, C., & Lipparini, F. (2024). Importance of Polarizable Embedding for Computing Optical Rotation: The Case of Camphor in Ethanol. The Journal of Physical Chemistry Letters, 7992–7999. https://doi.org/10.1021/acs.jpclett.4c01550
- Ruan, L., & Rybak, I. (2024). Stokes-Brinkman-Darcy models for coupled fluid-porous systems: derivation, analysis and validation. Appl. Math. Comp. (submitted).
- Schollenberger, T., von Wolff, L., Bringedal, C., Pop, I. S., Rohde, C., & Helmig, R. (2024). Investigation of Different Throat Concepts for Precipitation Processes in Saturated Pore-Network Models. Transport in Porous Media. https://doi.org/10.1007/s11242-024-02125-5
- Strohbeck, P., Discacciati, M., & Rybak, I. (2024). Optimized Schwarz method for the Stokes-Darcy problem with generalized interface conditions. J. Comput. Phys. (submitted).
- Strohbeck, P., & Rybak, I. (2024). Efficient preconditioners for coupled Stokes-Darcy problems with MAC scheme: Spectral analysis and numerical study. J. Sci. Comput. (submitted).
- Wendland, W. L. (2024). On the construction of the Stokes flow in a domain with cylindrical ends. Math. Meth. Appl. Sci., 1–6. https://doi.org/10.1002/mma.10106
- Wenzel, T., Haasdonk, B., Kleikamp, H., Ohlberger, M., & Schindler, F. (2024). Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling. In I. Lirkov & S. Margenov (Hrsg.), Large-Scale Scientific Computations (S. 117--125). Springer Nature Switzerland.
2023
- Afşer, H., Györfi, L., & Walk, H. (2023). Classification With Repeated Observations. IEEE Signal Processing Letters, 30, 1522–1526. https://doi.org/10.1109/LSP.2023.3326057
- Arridge, S. R., Burger, M., Hahn, B., & Quinto, E. T. (2023). Tomographic Inverse Problems: Mathematical Challenges and Novel Applications. Oberwolfach Reports, 20(2), Article 2. https://doi.org/10.4171/owr/2023/21
- Bamer, F., Ebrahem, F., Markert, B., & Stamm, B. (2023). Molecular Mechanics of Disordered Solids. Archives of Computational Methods in Engineering, 30(3), Article 3. https://doi.org/10.1007/s11831-022-09861-1
- Berberich, J., Scherer, C. W., & Allgower, F. (2023). Combining Prior Knowledge and Data for Robust Controller Design. IEEE Transactions on Automatic Control, 68(8), Article 8. https://doi.org/10.1109/tac.2022.3209342
- Beschle, C. A., & Barth, A. (2023). Quasi continuous level Monte Carlo for random elliptic PDEs.
- Brehmer, P., Herbst, M. F., Wessel, S., Rizzi, M., & Stamm, B. (2023). Reduced basis surrogates for quantum spin systems based on tensor networks. Physical Review E. https://doi.org/10.1103/PhysRevE.108.025306
- Brennenstuhl, M., Otto, R., Schembera, B., & Eicker, U. (2023). Optimized Dimensioning and Economic Assessment of Decentralized Hybrid Small Wind and PV Power Systems for Residential Buildings. https://www.researchsquare.com/article/rs-3677621/latest.pdf
- Buchfink, P., Glas, S., & Haasdonk, B. (2023). Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds. https://arxiv.org/abs/2312.00724
- 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
- Burbulla, S., Hörl, M., & Rohde, C. (2023). Flow in Porous Media with Fractures of Varying Aperture. SIAM J. Sci. Comput, 45(4), Article 4. https://doi.org/10.1137/22M1510406
- Cancès, E., Herbst, M. F., Kemlin, G., Levitt, A., & Stamm, B. (2023). Numerical stability and efficiency of response property calculations in density functional theory. Letters in Mathematical Physics. https://doi.org/10.1007/s11005-023-01645-3
- Cancès, E., Herbst, M. F., Kemlin, G., Levitt, A., & Stamm, B. (2023). Numerical stability and efficiency of response property calculations in density functional theory. Letters in Mathematical Physics, 113(1), Article 1. https://doi.org/10.1007/s11005-023-01645-3
- Cerejeiras, P., Ferreira, M., Kähler, U., & Wirth, J. (2023). Global Operator Calculus on Spin Groups. Journal of Fourier Analysis and Applications, 29(3), Article 3. https://doi.org/10.1007/s00041-023-10015-5
- Dippon, J., Gwinner, J., Khan, A. A., & Sama, M. (2023). A new regularized stochastic approximation framework for stochastic inverse problems. Nonlinear Anal. Real World Appl., 73, Paper No. 103869, 29. https://doi.org/10.1016/j.nonrwa.2023.103869
- Dusson, G., Sigal, I. M., & Stamm, B. (2023). Analysis of the Feshbach-Schur method for the Fourier spectral discretizations of Schrödinger operators. Mathematics of Computation, 92(340), Article 340. https://doi.org/10.1090/mcom/3774
- Eggenweiler, E., Nickl, J., & Rybak, I. (2023). Justification of generalized interface conditions for Stokes-Darcy problems. In E. Franck, J. Fuhrmann, V. Michel-Dansac, & L. Navoret (Hrsg.), Finite Volumes for Complex Applications X - Volume 1, Elliptic and Parabolic Problems (S. 275–283). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-40864-9_22
- Eggenweiler, E., & Rybak, I. (2023). Higher-order coupling conditions for arbitrary flows in Stokes-Darcy systems. J. Fluid Mech. (submitted).
- Fukuizumi, R., Gao, Y., Schneider, G., & Takahashi, M. (2023). Pattern formation in 2D stochastic anisotropic Swift-Hohenberg equation. Interdiscip. Inform. Sci., 29(1), Article 1. https://doi.org/10.4036/iis.2023.a.03
- Gander, M. J., Lunowa, S. B., & Rohde, C. (2023). Consistent and Asymptotic-Preserving Finite-Volume Robin Transmission Conditions for Singularly Perturbed Elliptic Equations. In S. C. Brenner, E. Chung, A. Klawonn, F. Kwok, J. Xu, & J. Zou (Hrsg.), Domain Decomposition Methods in Science and Engineering XXVI (S. 443--450). Springer International Publishing.
- 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), Article 1. https://doi.org/10.1137/21M1415005
- Gladbach, P., Jansen, J., & Lienstromberg, C. (2023). Non-Newtonian thin-film equations: global existence of solutions, gradient-flow structure and guaranteed lift-off. https://doi.org/10.48550/ARXIV.2301.10300
- Gramlich, D., Holicki, T., Scherer, C. W., & Ebenbauer, C. (2023). A Structure Exploiting SDP Solver for Robust Controller Synthesis. IEEE Control Syst. Lett., 7, 1831–1836. https://doi.org/10.1109/LCSYS.2023.3277314
- Gramlich, D., Pauli, P., Scherer, C. W., Allgöwer, F., & Ebenbauer, C. (2023). Convolutional Neural Networks as 2-D systems. https://doi.org/10.48550/ARXIV.2303.03042
- Gramlich, D., Scherer, C. W., Häring, H., & Ebenbauer, C. (2023). Synthesis of constrained robust feedback policies and model predictive control. https://doi.org/10.48550/ARXIV.2310.11404
- Griesemer, M., & Hofacker, M. (2023). On the weakness of short-range interactions in Fermi gases. Lett. Math. Phys., 113(1), Article 1. https://doi.org/10.1007/s11005-022-01624-0
- Györfi, L., Linder, T., & Walk, H. (2023). Lossless Transformations and Excess Risk Bounds in Statistical Inference. Entropy, 25(10), Article 10. https://doi.org/10.3390/e25101394
- Haas, T., de Rijk, B., & Schneider, G. (2023). Validity of Whitham’s modulation equations for dissipative systems with a conservation law: phase dynamics in a generalized Ginzburg-Landau system. Indiana Univ. Math. J., 72(1), Article 1. https://doi.org/10.1512/iumj.2023.72.9297
- Haasdonk, B., Kleikamp, H., Ohlberger, M., Schindler, F., & Wenzel, T. (2023). A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs. SIAM Journal on Scientific Computing, 45(3), Article 3. https://doi.org/10.1137/22m1493318
- Hahn, B., & Wirth, B. (2023). Convex reconstruction of moving particles with inexact motion model. PAMM, 23(2), Article 2. https://doi.org/10.1002/pamm.202300054
- Hahn, B. N., Quinto, E. T., & Rigaud, G. (2023). Foreword to special issue of Inverse Problems on modern challenges in imaging. Inverse Problems, 39(3), Article 3. https://doi.org/10.1088/1361-6420/acb569
- Hahn, B. N., Rigaud, G., & Schmähl, R. (2023). A class of regularizations based on nonlinear isotropic diffusion for inverse problems. IMA Journal of Numerical Analysis. https://doi.org/10.1093/imanum/drad002
- Hewing, L., Gramlich, D., Verhoek, C., Polonio, R., Veenman, J., Ardura, C., Tóth, R., Ebenbauer, C., Scherer, C., & Preda, V. (2023, Juli). Enhancing the Guidance, Navigation and Control of Autonomous Parafoils using Machine Learning Methods. Papers of ESA GNC-ICATT 2023. https://doi.org/10.5270/esa-gnc-icatt-2023-135
- Heß, M., & Schneider, G. (2023). A robust way to justify the derivative NLS approximation. Z. Angew. Math. Phys., 74(6), Article 6. https://doi.org/10.1007/s00033-023-02121-7
- Hilder, B., de Rijk, B., & Schneider, G. (2023). Moving modulating pulse and front solutions of permanent form in a FPU model with nearest and next-to-nearest neighbor interaction. SIAM J. Appl. Dyn. Syst., 22(2), Article 2. https://doi.org/10.1137/22M1502902
- Hilder, B., de Rijk, B., & Schneider, G. (2023). Nonlinear stability of periodic roll solutions in the real Ginzburg-Landau equation against $C_ub^m$-perturbations. Comm. Math. Phys., 400(1), Article 1. https://doi.org/10.1007/s00220-022-04619-z
- Holicki, T., & Scherer, C. W. (2023). IQC based analysis and estimator design for discrete-time systems affected by impulsive uncertainties. Nonlinear Anal. Hybri., 50, 101399. https://doi.org/10.1016/j.nahs.2023.101399
- Holicki, T., & Scherer, C. W. (2023). Input-Output-Data-Enhanced Robust Analysis via Lifting. IFAC-PapersOnLine, 56(2), Article 2. https://doi.org/10.1016/j.ifacol.2023.10.047
- Holzmüller, D., Zaverkin, V., Kästner, J., & Steinwart, I. (2023). A Framework and Benchmark for Deep Batch Active Learning for Regression. Journal of Machine Learning Research, 24(164), Article 164. http://jmlr.org/papers/v24/22-0937.html
- Hornischer, N. (2023). Model Order Reduction with Dynamically Transformed Modes for Electrophysiological Simulations. GAMM Archive for Students.
- Horsch, M. T., Schembera, B., & Preisig, H. A. (2023). European standardization efforts from FAIR toward explainable-AI-ready data documentation in materials modelling. Proc. ICAPAI. https://www.researchgate.net/profile/Martin-Horsch/publication/370285356_European_standardization_efforts_from_FAIR_toward_explainable-AI-ready_data_documentation_in_materials_modelling/links/644934045762c95ac3528653/European-standardization-efforts-from-FAIR-toward-explainable-AI-ready-data-documentation-in-materials-modelling.pdf
- Horsch, M., Schembera, B., & DFG, M. (2023). Epistemic metadata in molecular modelling: First-stage case-study report (10 cases). In Inprodat eV, Kaiserslautern, Tech. Rep (Inprodat eV, Kaiserslautern, Tech. Rep). https://www.researchgate.net/profile/Martin-Horsch/publication/366974408_Epistemic_metadata_in_molecular_modelling_First-stage_case-study_report_10_cases/links/63bc41e4a03100368a6645a6/Epistemic-metadata-in-molecular-modelling-First-stage-case-study-report-10-cases.pdf
- Jansen, J., Lienstromberg, C., & Nik, K. (2023). Long-Time Behavior and Stability for Quasilinear Doubly Degenerate Parabolic Equations of Higher Order. SIAM Journal on Mathematical Analysis, 55(2), Article 2. https://doi.org/10.1137/22M1491137
- Jha, A., John, V., & Knobloch, P. (2023). Adaptive Grids in the Context of Algebraic Stabilizations for Convection-Diffusion-Reaction Equations. SIAM Journal on Scientific Computing, 45(4), Article 4. https://doi.org/10.1137/21m1466360
- Jha, A., Nottoli, M., Mikhalev, A., Quan, C., & Stamm, B. (2023). Linear Scaling Computation of Forces for the Domain-Decomposition Linear Poisson--Boltzmann Method. The Journal of Chemical Physics, 158, 104105. https://doi.org/10.1063/5.0141025
- Keckstein, S., Dippon, J., Hudelist, G., Koninckx, P., Condous, G., Schroeder, L., & Keckstein, J. (2023). Sonomorphologic Changes in Colorectal Deep Endometriosis: The Long-Term Impact of Age and Hormonal Treatment. Ultraschall in der Medizin - European Journal of Ultrasound, EFirst, Article EFirst. https://doi.org/10.1055/a-2209-5653
- Keim, J., Schwarz, A., Chiocchetti, S., Rohde, C., & Beck, A. (2023). A Reinforcement Learning Based Slope Limiter for Two-Dimensional Finite Volume Schemes. https://doi.org/10.13140/RG.2.2.18046.87363
- 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
- Kharitenko, A., & Scherer, C. (2023). Time-varying Zames–Falb multipliers for LTI Systems are superfluous. Automatica, 147, 110577. https://doi.org/10.1016/j.automatica.2022.110577
- Kohr, M., Nistor, V., & Wendland, W. L. (2023). Layer potentials and essentially translation invariant pseudodifferential operators on manifolds with cylindrical ends. In Postpandemic Operator Theory (S. 61–115). Springer-Verlag Berlin. https://doi.org/10.48550/arXiv.2308.06308
- Kröker, I., Oladyshkin, S., & Rybak, I. (2023). Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems. Comput. Geosci. https://doi.org/10.1007/s10596-023-10236-z
- Lienstromberg, C., Schiffer, S., & Schubert, R. (2023). A data-driven approach to viscous fluid mechanics: the stationary case. Arch. Ration. Mech. Anal., 247(2), Article 2. https://doi.org/10.1007/s00205-023-01849-w
- Lienstromberg, C., Schiffer, S., & Schubert, R. (2023). A variational approach to the non-newtonian Navier-Stokes equations. https://doi.org/doi:10.48550/ARXIV.2312.03546
- Lienstromberg, C., & Velázquez, J. J. L. (2023). Long-time asymptotics and regularity estimates for weak solutions to a doubly degenerate thin-film equation in the Taylor-Couette setting. arXiv. https://doi.org/10.48550/ARXIV.2203.00075
- Maier, D., Reichel, W., & Schneider, G. (2023). Breather solutions for a semilinear Klein-Gordon equation on a periodic metric graph. J. Math. Anal. Appl., 528(2), Article 2. https://doi.org/10.1016/j.jmaa.2023.127520
- Meijer, T. J., Holicki, T., Eijnden, S. J. A. M. van den, Scherer, C. W., & Heemels, W. P. M. H. (2023). The Non-Strict Projection Lemma. arXiv. https://doi.org/10.48550/ARXIV.2305.08735
- Mel’nyk, T. (2023). Complex Analysis (No. 1; Nummer 1). Springer Cham. https://doi.org/10.1007/978-3-031-39615-1
- Mel’nyk, T. A. (2023). Asymptotic analysis of spectral problems in thick junctions with the branched fractal structure. Mathematical Methods in the Applied Sciences, 46(3), Article 3. https://doi.org/10.1002/mma.8692
- Merkle, R., & Barth, A. (2023). On Properties and Applications of Gaussian Subordinated Lévy Fields. Methodology and Computing in Applied Probability, 25, 62. https://doi.org/10.1007/s11009-023-10033-2
- Miller, C. T., Gray, W. G., Kees, C. E., Rybak, I., & Shepherd, B. J. (2023). Correction to: Modelling Sediment Transport in Three-Phase Surface Water Systems. J. Hydraul. Res., 61, 168–171. https://doi.org/10.1080/00221686.2022.2107580
- Mohammadi, F., Eggenweiler, E., Flemisch, B., Oladyshkin, S., Rybak, I., Schneider, M., & Weishaupt, K. (2023). A Surrogate-Assisted Uncertainty-Aware Bayesian Validation Framework and its Application to Coupling Free Flow and Porous-Medium Flow. Comput. Geosci. https://doi.org/10.1007/s10596-023-10228-z
- Morato, M. M., Holicki, T., & Scherer, C. W. (2023). Stabilizing Model Predictive Control Synthesis using Integral Quadratic Constraints and Full-Block Multipliers. Int. J. Robust Nonlin. https://doi.org/10.1002/rnc.6952
- Nagy, P.-A., & Semmelmann, U. (2023). Eigenvalue estimates for 3-Sasaki structures.
- Nottoli, M., Bondanza, M., Mazzeo, P., Cupellini, L., Curutchet, C., Loco, D., Lagardère, L., Piquemal, J., Mennucci, B., & Lipparini, F. (2023). QM/AMOEBA description of properties and dynamics of embedded molecules. WIREs Computational Molecular Science, 13(6), Article 6. https://doi.org/10.1002/wcms.1674
- Pelinovsky, D., & Schneider, G. (2023). KP-II approximation for a scalar Fermi-Pasta-Ul system on a 2D square lattice. SIAM J. Appl. Math., 83(1), Article 1. https://doi.org/10.1137/22M1509369
- Pes, F., Polack, É., Mazzeo, P., Dusson, G., Stamm, B., & Lipparini, F. (2023). A Quasi Time-Reversible Scheme Based on Density Matrix Extrapolation on the Grassmann Manifold for Born–Oppenheimer Molecular Dynamics. The Journal of Physical Chemistry Letters, 9720--9726. https://doi.org/10.1021/acs.jpclett.3c02098
- Ruan, L., & Rybak, I. (2023). Stokes-Brinkman-Darcy models for coupled free-flow and porous-medium systems. In E. Franck, J. Fuhrmann, V. Michel-Dansac, & L. Navoret (Hrsg.), Finite Volumes for Complex Applications X - Volume 1, Elliptic and Parabolic Problems (S. 365–373). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-40864-9_31
- Rösinger, C. A., & Scherer, C. W. (2023). Gain-Scheduling Controller Synthesis for Networked Systems with Full Block Scalings. https://doi.org/10.1109/TAC.2023.3329851
- Rösinger, C. A., & Scherer, C. W. (2023). Gain-Scheduling Controller Synthesis for Nested Systems With Full Block Scalings. IEEE Transactions on Automatic Control, 1–16. https://doi.org/10.1109/TAC.2023.3329851
- Santin, G., Wenzel, T., & Haasdonk, B. (2023). On the optimality of target-data-dependent kernel greedy interpolation in Sobolev Reproducing Kernel Hilbert Spaces. https://arxiv.org/abs/2307.09811
- Schembera, B., Wübbeling, F., Koprucki, T., Biedinger, C., Reidelbach, M., Schmidt, B., Göddeke, D., & Fiedler, J. (2023). Building Ontologies and Knowledge Graphs for Mathematics and its Applications. Proceedings of the Conference on Research Data Infrastructure, 1. https://doi.org/10.52825/cordi.v1i.255
- Scherer, C. W. (2023). Robust Exponential Stability and Invariance Guarantees with General Dynamic O’Shea-Zames-Falb Multipliers. https://doi.org/10.48550/ARXIV.2306.00571
- Scherer, C. W., Ebenbauer, C., & Holicki, T. (2023). Optimization Algorithm Synthesis based on Integral Quadratic Constraints: A Tutorial. https://doi.org/10.48550/ARXIV.2306.00565
- Schwahn, P., Semmelmann, U., & Weingart, G. (2023). Stability of the Non-Symmetric Space $E_7/PSO(8)$.
- Seus, D., Radu, F. A., & Rohde, C. (2023). Towards hybrid two-phase modelling using linear domain decomposition. Numer. Methods Partial Differential Equations, 39(1), Article 1. 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., 147(3), Article 3. https://doi.org/10.1007/s11242-023-01919-3
- Strohbeck, P., Riethmüller, C., Göddeke, D., & Rybak, I. (2023). Robust and efficient preconditioners for Stokes-Darcy problems. In E. Franck, J. Fuhrmann, V. Michel-Dansac, & L. Navoret (Hrsg.), Finite Volumes for Complex Applications X - Volume 1, Elliptic and Parabolic Problems (S. 375–383). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-40864-9_32
- Taha, F. A., Yan, S., & Bitar, E. (2023). A Distributionally Robust Approach to Regret Optimal Control using the Wasserstein Distance. 2023 62nd IEEE Conference on Decision and Control (CDC), 2768–2775. https://doi.org/10.1109/CDC49753.2023.10384311
- Theisen, L., & Stamm, B. (2023). A Scalable Two-Level Domain Decomposition Eigensolver for Periodic Schrödinger Eigenstates in Anisotropically Expanding Domains. https://doi.org/10.48550/arXiv.2311.08757
- Wendland, W. L. (2023). My relation with GAMM (G. Rundbrief, Hrsg.; No. 1). GAMM Rundbrief. https://www.gamm.org/wp-content/uploads/2024/03/GAMM_1-23_web.pdf
- Wenzel, T., Santin, G., & Haasdonk, B. (2023). Analysis of Target Data-Dependent Greedy Kernel Algorithms: Convergence Rates for f -, f · P - and f /P -greedy. Constructive Approximation, 57(1), Article 1. https://doi.org/10.1007/s00365-022-09592-3
- Wenzel, T., Santin, G., & Haasdonk, B. (2023). Stability of convergence rates: Kernel interpolation on non-Lipschitz domains (2024 IMA Journal of Numerical Analysis, 44(3):1-22, Hrsg.). https://doi.org/10.1093/imanum/drae014
- Zaverkin, V., Holzmüller, D., Bonfirraro, L., & Kästner, J. (2023). Transfer learning for chemically accurate interatomic neural network potentials. Phys. Chem. Chem. Phys., 25(7), Article 7. https://doi.org/10.1039/D2CP05793J
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), Article 2. https://doi.org/10.1177/10943420211055188
- Assenmacher, O., Bruell, G., & Lienstromberg, C. (2022). Non-Newtonian two-phase thin-film problem: local existence, uniqueness, and stability. Comm. Partial Differential Equations, 47(1), Article 1. https://doi.org/10.1080/03605302.2021.1957929
- Barth, A., & Stein, A. (2022). Numerical analysis for time-dependent advection-diffusion problems with random discontinuous coefficients. ESAIM: M2AN, 56(5), Article 5. https://doi.org/10.1051/m2an/2022054
- Benner, P., Burger, M., Göddeke, D., Görgen, C., Himpe, C., Heiland, J., Koprucki, T., Ohlberger, M., Rave, S., Reiselbach, M., Saak, J., Schöbel, A., Tabelow, K., & Weber, M. (2022). Die mathematische Forschungsdateninitiative in der NFDI: MaRDI (Mathematical Research Data Initiative). GAMM Rundbrief, 2022(1), Article 1.
- Berberich, J., Scherer, C. W., & Allgower, F. (2022). Combining Prior Knowledge and Data for Robust Controller Design. IEEE Transactions on Automatic Control, 1--16. https://doi.org/10.1109/tac.2022.3209342
- 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., & Barth, A. (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., Dedner, A., Hörl, M., & Rohde, C. (2022). Dune-MMesh: The Dune Grid Module for Moving Interfaces. J. Open Source Softw., 7(74), Article 74. https://doi.org/10.21105/joss.03959
- 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
- Cekić, M., Lefeuvre, T., Moroianu, A., & Semmelmann, U. (2022). Towards Brin’s conjecture on frame flow ergodicity: new progress and perspectives.
- Dusson, G., Sigal, I., & Stamm, B. (2022). Analysis of the Feshbach–Schur method for the Fourier spectral discretizations of Schrödinger operators. Mathematics of Computation, 92(339), Article 339. https://doi.org/10.1090/mcom/3774
- Echterdiek, F., Kitterer, D., Dippon, J., Ott, M., Paul, G., Latus, J., & Schwenger, V. (2022). Outcome of kidney transplantations from ≥65‐year‐old deceased donors with acute kidney injury. Clinical Transplantation, 36(5), Article 5. https://doi.org/10.1111/ctr.14612
- Echterdiek, F., Tilgener, C., Dippon, J., Kitterer, D., Scheder-Bieschin, J., Paul, G., Ott, M., Humke, U., Schwenger, V., & Latus, J. (2022). Impact of the explanting surgeon’s impression of donor arteriosclerosis on outcome of kidney transplantations from donors aged ≥65 years. Langenbeck’s Archives of Surgery, 407(2), Article 2. https://doi.org/10.1007/s00423-021-02383-7
- 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
- Fiedler, C., Scherer, C. W., & Trimpe, S. (2022, Dezember). Learning Functions and Uncertainty Sets Using Geometrically Constrained Kernel Regression. 61st IEEE Conf. Decision and Control. https://doi.org/10.1109/cdc51059.2022.9993144
- Focks, T., Bamer, F., Markert, B., Wu, Z., & Stamm, B. (2022). Displacement field splitting of defective hexagonal lattices. Physical Review B. https://doi.org/10.1103/PhysRevB.106.014105
- Frank, R. L., Laptev, A., & Weidl, T. (2022). An improved one-dimensional Hardy inequality. J. Math. Sci. (N.Y.), 268(3, Problems in mathematical analysis. No. 118), Article 3, Problems in mathematical analysis. No. 118. https://doi.org/10.1007/s10958-022-06199-8
- Frank, R., Laptev, A., & Weidl, T. (2022). Schrödinger Operators: Eigenvalues and Lieb–Thirring Inequalities. In Cambridge Studies in Advanced Mathematics (S. 512).
- Fukuizumi, R., & Schneider, G. (2022). Interchanging space and time in nonlinear optics modeling and dispersion management models. J. Nonlinear Sci., 32(3), Article 3. https://doi.org/10.1007/s00332-022-09788-8
- 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.
- Gilg, S., Schneider, G., & Uecker, H. (2022). Nonlinear dynamics of modulated waves on graphene like quantum graphs. Math. Nachr., 295(11), Article 11. https://doi.org/10.1002/mana.202100009
- Gramlich, D., Ebenbauer, C., & Scherer, C. W. (2022). Synthesis of Accelerated Gradient Algorithms for Optimization and Saddle Point Problems using Lyapunov functions. Syst. Control Lett., 165. https://arxiv.org/abs/2006.09946
- Gramlich, D., Scherer, C. W., & Ebenbauer, C. (2022). Robust Differential Dynamic Programming. 61st IEEE Conf. Decision and Control. https://doi.org/10.1109/cdc51059.2022.9992569
- 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
- Griesemer, M., & Hofacker, M. (2022). From Short-Range to Contact Interactions in Two-dimensional Many-Body Quantum Systems. Annales Henri Poincaré, 23(8), Article 8. https://doi.org/10.1007/s00023-021-01149-7
- 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), Article 0. https://doi.org/10.3934/ipi.2022018
- Hassan, M., Williamson, C., Baptiste, J., Braun, S., Stace, A. J., Besley, E., & Stamm, B. (2022). Manipulating Interactions between Dielectric Particles with Electric Fields : A General Electrostatic Many-Body Framework. Journal of Chemical Theory and Computation, 18(10), Article 10. https://doi.org/10.1021/acs.jctc.2c00008
- Hilder, B. (2022). Modulating traveling fronts in a dispersive Swift-Hohenberg equation coupled to an additional conservation law. J. Math. Anal. Appl., 513(2), Article 2. https://doi.org/10.1016/j.jmaa.2022.126224
- Hilder, B., & Sharma, U. (2022). Quantitative coarse-graining of Markov chains.
- Holicki, T. (2022). A Complete Analysis and Design Framework for Linear Impulsive and Related Hybrid Systems [University of Stuttgart]. https://doi.org/10.18419/opus-12158
- Holicki, T., & Scherer, C. W. (2022). A Dynamic S-Procedure for Dynamic Uncertainties. IFAC-PapersOnline, 55(25), Article 25. https://doi.org/10.1016/j.ifacol.2022.09.331
- Holicki, T., & Scherer, C. W. (2022). IQC Based Analysis and Estimator Design for Discrete-Time Systems Affected by Impulsive Uncertainties.
- Holicki, T., & Scherer, C. W. (2022). Input-Output-Data-Enhanced Robust Analysis via Lifting.
- Holzmüller, D., & Steinwart, I. (2022). Training two-layer ReLU networks with gradient descent is inconsistent. Journal of Machine Learning Research, 23(181), Article 181. http://jmlr.org/papers/v23/20-830.html
- Hornischer, N. (2022). Model Order Reduction with Transformed Modes for Electrophysiological Simulations [Bathesis].
- 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), Article 4–5. https://doi.org/10.1515/itit-2022-0033
- Hägele, D., Schulz, C., Beschle, C., Booth, H., Butt, M., Barth, A., Deussen, O., & Weiskopf, D. (2022). Uncertainty visualization : Fundamentals and recent developments. Information Technology, 64(4–5), Article 4–5. 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
- Kharitenko, A., & Scherer, C. W. (2022). On the exactness of a stability test for Lur’e systems with slope-restricted nonlinearities.
- Klink, M. (2022). Time Error Estimators and Adaptive Time-stepping Schemes [Bathesis].
- Klumpp, M., & Schneider, G. (2022). The Schrödinger approximation for the Helmholtz equation if the refractive index is a step function. Wave Motion, 110, Paper No. 102891, 6. https://doi.org/10.1016/j.wavemoti.2022.102891
- Klumpp, M., & Schneider, G. (2022). A note on the validity of the Schrödinger approximation for the Helmholtz equation. J. Appl. Anal., 28(1), Article 1. https://doi.org/10.1515/jaa-2021-2058
- 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), Article 1, 126464. https://doi.org/10.1016/j.jmaa.2022.126464
- 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.
- Lienstromberg, C., Pernas-Casta\ no, T., & Velázquez, J. J. L. (2022). Analysis of a two-fluid Taylor-Couette flow with one non-Newtonian fluid. J. Nonlinear Sci., 32(2), Article 2. https://doi.org/10.1007/s00332-021-09750-0
- Lienstromberg, C., Pernas-Casta\no, T., & Velázquez, J. J. L. (2022). Analysis of a two-fluid Taylor-Couette flow with one non-Newtonian fluid. J. Nonlinear Sci., 32(2), Article 2. https://doi.org/10.1007/s00332-021-09750-0
- Lienstromberg, C., Schiffer, S., & Schubert, R. (2022). A data-driven approach to viscous fluid mechanics -- the stationary case. https://doi.org/10.48550/ARXIV.2207.00324
- 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 (K. Schulte, C. Tropea, & B. Weigand, Hrsg.; S. 67–86). Springer International Publishing. https://doi.org/10.1007/978-3-031-09008-0_4
- Maier, B., Göddeke, D., Huber, F., Klotz, T., Röhrle, O., & Schulte, M. (2022). OpenDiHu: An Efficient and Scalable Framework for Biophysical Simulations of the Neuromuscular System.
- 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., & Klevtsovskiy, A. V. (2022). Asymptotic expansion for the solution of a convection-diffusion problem in a thin graph-like junction. Asymptotic Analysis, 130(3–4), Article 3–4. https://doi.org/10.3233/ASY-221761
- 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). On some distributional properties of subordinated Gaussian random fields. Methodol Comput Appl Probab.
- 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
- Mikhalev, A., Nottoli, M., & Stamm, B. (2022). Linearly scaling computation of ddPCM solvation energy and forces using the fast multipole method. The Journal of Chemical Physics, 157(11), Article 11. https://doi.org/10.1063/5.0104536
- Nitzsche, M., Albers, H., Kluth, T., & Hahn, B. (2022). Compensating model imperfections during image reconstruction via Resesop. International Journal on Magnetic Particle Imaging, Vol 8 No 1 Suppl 1 (2022). https://doi.org/10.18416/IJMPI.2022.2203062
- Nottoli, M., Mikhalev, A., Stamm, B., & Lipparini, F. (2022). Coarse-Graining ddCOSMO through an Interface between Tinker and the ddX Library. The Journal of Physical Chemistry B, 126(43), Article 43. https://doi.org/10.1021/acs.jpcb.2c04579
- 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
- Rösinger, C. A., & Scherer, C. W. (2022). Gain-Scheduling Controller Synthesis for Networked Systems with Full Block Scalings.
- Santin, G., Karvonen, T., & Haasdonk, B. (2022). Sampling based approximation of linear functionals in reproducing kernel Hilbert spaces. BIT Numerical Mathematics, 62(1), Article 1. https://doi.org/10.1007/s10543-021-00870-3
- Scherer, C. (2022). Dissipativity and Integral Quadratic Constraints, Tailored computational robustness tests for complex interconnections. IEEE Control Systems Magazine, 42(3), Article 3. https://arxiv.org/abs/2105.07401
- Scherer, C. W. (2022). Dissipativity, Convexity and Tight O\textquotesingleShea-Zames-Falb Multipliers for Safety Guarantees. IFAC-PapersOnLine, 55(30), Article 30. https://doi.org/10.1016/j.ifacol.2022.11.044
- Schneider, G., & Winter, M. (2022). The amplitude system for a simultaneous short-wave Turing and long-wave Hopf instability. Discrete Contin. Dyn. Syst. Ser. S, 15(9), Article 9. https://doi.org/10.3934/dcdss.2021119
- Schneider, G., & Winter, M. (2022). The amplitude system for a imultaneous short-wave Turing and long-wave Hopf instability. Discrete Contin. Dyn. Syst. Ser. S, 15(9), Article 9. https://doi.org/10.3934/dcdss.2021119
- 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.
- Stamm, B., & Theisen, L. (2022). A Quasi-Optimal Factorization Preconditioner for Periodic Schrödinger Eigenstates in Anisotropically Expanding Domains. SIAM Journal on Numerical Analysis, 60(5), Article 5. https://doi.org/10.1137/21m1456005
- 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., 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.
- 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
- 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), Article 11. 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
- Wittwar, D., & Haasdonk, B. (o. J.). Convergence rates for matrix P-greedy variants. In Numerical mathematics and advanced applications---ENUMATH 2019 (Bd. 139, S. 1195--1203). Springer, Cham. https://doi.org/10.1007/978-3-030-55874-1\_119
- 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), Article 6. 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), Article 8. 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), Article 4. 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), Article 1. https://doi.org/10.1214/21-EJS1845
- Brencher, L., & Barth, A. (2021). Stochastic conservation laws with discontinuous flux functions: The multidimensional case.
- Brencher, L., & Barth, A. (2021). Scalar conservation laws with stochastic discontinuous flux function. ArXiv e-prints, arXiv:2107.00549 math.NA.
- 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., & 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
- 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), Article 1.
- 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), Article 2. 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). Greedy sampling and approximation for realizing feedback control for high dimensional nonlinear systems.
- 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
- 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), Article 8. https://ojs.aaai.org/index.php/AAAI/article/view/16912
- Fiedler, C., Scherer, C. W., & Trimpe, S. (2021). Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees. 60th IEEE Conf. Decision and Control, 5122–5129. https://arxiv.org/abs/2105.03397
- 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), Article 1. 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), Article 2. 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. (2021). Motion compensation strategies in tomography. https://doi.org/10.1007/978-3-030-57784-1_3
- 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
- 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, Article 55. 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), Article 8. https://doi.org/10.1088/1361-6544/abd612
- 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). 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), Article 2. https://doi.org/10.1109/LCSYS.2020.3004506
- 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), Article 0. 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), Article 1. 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), Article 12. 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), Article 9. 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), Article 12. https://doi.org/10.1002/mma.7167
- 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
- Leiteritz, R., Buchfink, P., Haasdonk, B., & Pflüger, D. (2021). Surrogate-data-enriched Physics-Aware Neural Networks.
- 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. (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), Article 2. https://doi.org/10.1111/jtsa.12560
- Mehl, L., Beschle, C., Barth, A., & Bruhn, A. (2021). An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. Proceedings of the International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 140--152. https://doi.org/10.1007/978-3-030-75549-2_12
- Mel’nyk, T. (2021). Asymptotic approximations for eigenvalues and eigenfunctions of a spectral problem in a thin graph-like junction with a concentrated mass in the node. Analysis and Applications, 19(05), Article 05. https://doi.org/10.1142/S0219530520500219
- Michalowsky, S., Scherer, C., & Ebenbauer, C. (2021). Robust and structure exploiting optimisation algorithms: An integral quadratic constraint approach. International Journal of Control, 94(11), Article 11. https://doi.org/10.1080/00207179.2020.1745286
- 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., & Tang, H. (2021). On the stochastic Dullin-Gottwald-Holm equation: global existence and wave-breaking phenomena. NoDEA Nonlinear Differential Equations Appl., 28(1), Article 1. 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. Dynam. Differential Equations, 33, 1823–1852. https://doi.org/10.1007/s10884-020-09872-1
- Rohde, C., & Von Wolff, L. (2021). A ternary Cahn–Hilliard–Navier–Stokes model for two-phase flow with precipitation and dissolution. Mathematical Models and Methods in Applied Sciences, 31(01), Article 01. https://doi.org/10.1142/S0218202521500019
- 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), Article 5. https://doi.org/10.1088/1361-6420/abd85a
- Santin, G., & Haasdonk, B. (2021). Kernel methods for surrogate modeling. In P. Benner, W. Schilders, S. Grivet-Talocia, A. Quarteroni, G. Rozza, & L. M. Silveira (Hrsg.), Model Order Reduction: Bd. 1: System-and Data-Driven Methods and Algorithms (S. 311–354). de Gruyter.
- Scherer, C., & Ebenbauer, C. (2021). Convex Synthesis of Accelerated Gradient Algorithms. SIAM J. Contr. Optim. (to appear). https://arxiv.org/abs/2102.06520
- Schmalfuss, J., Riethmüller, C., Altenbernd, M., Weishaupt, K., & Göddeke, D. (2021). Partitioned coupling vs. monolithic block-preconditioning approaches for solving Stokes-Darcy systems. Proceedings of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS). https://doi.org/10.23967/coupled.2021.043
- 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
- 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
- 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), Article 8. https://doi.org/10.1016/j.ifacol.2021.08.583
- von Wolff, L. (2021). The Dune-Phasefield Module release 1.0. DaRUS. https://doi.org/10.18419/darus-1634
- 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. Transport in Porous Media, 137(2), Article 2. 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., 138, 1–23. 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.
- Wenzel, T., Santin, G., & Haasdonk, B. (2021). Universality and Optimality of Structured Deep Kernel Networks. arXiv. https://doi.org/10.48550/ARXIV.2105.07228
- Wenzel, T., Santin, G., & Haasdonk, B. (2021). Analysis of target data-dependent greedy kernel algorithms: Convergence rates for $f$-, $f P$- and $f/P$-greedy. arXiv. https://doi.org/10.48550/ARXIV.2105.07411
- Wenzel, T., Santin, G., & Haasdonk, B. (2021). Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, f P- and f/P-greedy. arXiv. https://doi.org/10.48550/ARXIV.2105.07411
- Zaverkin, V., Kästner, J., Holzmüller, D., & Steinwart, I. (2021). Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments. J. Chem. Theory Comput. https://doi.org/10.1021/acs.jctc.1c00527
2020
- Alla, A., Haasdonk, B., & Schmidt, A. (2020). Feedback control of parametrized PDEs via model order reduction and dynamic programming principle. Adv. Comput. Math., 46(1), Article 1. https://doi.org/10.1007/s10444-020-09744-8
- 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), Article 2. 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. (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.
- 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), Article 4.
- 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), Article 4. 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), Article 12. 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
- Brencher, L., & Barth, A. (2020). Hyperbolic Conservation Laws with Stochastic Discontinuous Flux Functions. International Conference on Finite Volumes for Complex Applications, 265--273.
- Bringedal, C., Von Wolff, L., & Pop, I. S. (2020). Phase Field Modeling of Precipitation and Dissolution Processes in Porous Media: Upscaling and Numerical Experiments. Multiscale Modeling &$\mathsemicolon$ Simulation, 18(2), Article 2. https://doi.org/10.1137/19m1239003
- 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), Article 7. 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), Article 1. 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
- Escher, J., Knopf, P., Lienstromberg, C., & Matioc, B.-V. (2020). Stratified periodic water waves with singular density gradients. Ann. Mat. Pura Appl. (4), 199(5), Article 5. https://doi.org/10.1007/s10231-020-00950-1
- IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22-25, 2018: MORCOS 2018. (2020). In J. Fehr & B. Haasdonk (Hrsg.), IUTAM Bookseries. Springer.
- Fischer, S., & Steinwart, I. (2020). Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm. J. Mach. Learn. Res., 205, Article 205.
- Fischer, S., & Steinwart, I. (2020). Sobolev norm learning rates for regularized least-squares algorithms. J. Mach. Learn. Res., 21(205), Article 205. http://jmlr.org/papers/v21/19-734.html
- Geck, M. (2020). Green functions and Glauberman degree-divisibility. Annals of Mathematics, 192(1), Article 1. https://doi.org/10.4007/annals.2020.192.1.4
- 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
- Geck, M. (2020). ChevLie: Constructing Lie algebras and Chevalley groups. Journal of Software for Algebra and Geometry, 10(1), Article 1. https://doi.org/10.2140/jsag.2020.10.41
- Geck, M. (2020). On Jacob’s construction of the rational canonical form of a matrix. The Electronic Journal of Linear Algebra, 36(36), Article 36. 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
- 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). 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.), Hyperbolic Problems: Theory, Numerics, Applications. Proceedings of the Seventeenth International Conference on Hyperbolic Problems 2018 (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
- 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), Article 2. https://doi.org/10.1093/imanum/drz004
- 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), Article 3. 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), Article 2. https://doi.org/10.1007/s11040-020-09344-4
- Grunert, D., Fehr, J., & Haasdonk, B. (2020). Well-scaled, a-posteriori error estimation for model order reduction of large second-order mechanical systems. ZAMM, 100(8), Article 8. https://doi.org/10.1002/zamm.201900186
- Göddeke, D., Schirwon, M., & Borg, N. (2020). Smartphone-Apps im Mathematikstudium. https://doi.org/10.18419/darus-1147
- Haas, T., de Rijk, B., & Schneider, G. (2020). MODULATION EQUATIONS NEAR THE ECKHAUS BOUNDARY: THE KdV EQUATION. SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 52(6), Article 6. 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
- Haasdonk, B., Hamzi, B., Santin, G., & Wittwar, D. (2020). Greedy kernel methods for center manifold approximation. In Spectral and high order methods for partial differential equations---ICOSAHOM 2018 (Bd. 134, S. 95--106). Springer, Cham. https://doi.org/10.1007/978-3-030-39647-3\_6
- 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), Article 5. 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), Article 2. 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
- Häufle, D. F. B., Wochner, I., Holzmüller, D., Driess, D., Günther, M., & Schmitt, S. (2020). Muscles Reduce Neuronal Information Load : Quantification of Control Effort in Biological vs. Robotic Pointing and Walking. Frontiers In Robotics and AI, 7, 77. https://doi.org/10.3389/frobt.2020.00077
- Jentsch, T., & Weingart, G. (2020). RIEMANNIAN AND KAHLERIAN NORMAL COORDINATES. ASIAN JOURNAL OF MATHEMATICS, 24(3), Article 3.
- 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), Article 2.
- 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), Article 1. 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), Article 07. https://doi.org/10.1142/s0129167x20500512
- Lienstromberg, C., & Müller, S. (2020). Local strong solutions to a quasilinear degenerate fourth-order thin-film equation. NoDEA Nonlinear Differential Equations Appl., 27(2), Article 2. https://doi.org/10.1007/s00030-020-0619-x
- 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). Construction of breather solutions for nonlinear Klein-Gordon equations on periodic metric graphs. JOURNAL OF DIFFERENTIAL EQUATIONS, 268(6), Article 6. https://doi.org/10.1016/j.jde.2019.09.035
- Maier, D. (2020). BREATHER SOLUTIONS ON DISCRETE NECKLACE GRAPHS. OPERATORS AND MATRICES, 14(3), Article 3. https://doi.org/10.7153/oam-2020-14-48
- 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), Article 1. https://doi.org/10.1515/forum-2018-0188
- Nagy, P.-A., & Semmelmann, U. (2020). Conformal Killing forms in Kaehler geometry.
- 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), Article 4. 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., 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). Compressible multicomponent flow in porous media with Maxwell-Stefan diffusion. Math. Meth. Appl. Sci., 43(7), Article 7. https://doi.org/10.1002/mma.6185
- 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), Article 7. 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), Article 6. 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), Article 2. https://doi.org/10.1016/j.ifacol.2020.12.570
- Rösinger, C. A., & Scherer, C. W. (2020). A Flexible Synthesis Framework of Structured Controllers for Networked Systems. IEEE Trans. Control Netw. Syst., 7(1), Article 1. https://doi.org/10.1109/TCNS.2019.2914411
- Schneider, G. (2020). The KdV approximation for a system with unstable resonances. Math. Methods Appl. Sci., 43(6), Article 6.
- Semmelmann, U., Wang, C., & Wang, M. Y.-K. (2020). On the linear stability of nearly Kähler 6-manifolds. Ann. Global Anal. Geom., 57(1), Article 1. https://doi.org/10.1007/s10455-019-09686-5
- Stein, A., & Barth, A. (2020). A Multilevel Monte Carlo Algorithm for Parabolic Advection-Diffusion Problems with Discontinuous Coefficients. In B. Tuffin & P. L’Ecuyer (Hrsg.), Monte Carlo and Quasi-Monte Carlo Methods (Bd. 324, S. 445--466). Springer International Publishing. https://doi.org/10.1007/978-3-030-43465-6_22
- 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), Article 1. 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), Article 1–2. 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), Article 2. 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), Article 1. 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), Article 1. https://doi.org/10.1017/S0308210518000227
- 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
- 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
- Bianchi, L. A., Blömker, D., & Schneider, G. (2019). Modulation equation and SPDEs on unbounded domains. Commun. Math. Phys., 371(1), Article 1.
- 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), Article 2. 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), Article 3. https://doi.org/10.1137/18M1174362
- Chirilus-Bruckner, M., Maier, D., & Schneider, G. (2019). Diffusive stability for periodic metric graphs. Math. Nachr., 292(6), Article 6.
- Colombo, R. M., LeFloch, P. G., Rohde, C., & Trivisa, K. (2019). Nonlinear Hyperbolic Problems: Modeling, Analysis, and Numerics. Oberwohlfach Rep., 16, Article 16. 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), Article 1. 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), Article 44. 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), Article 1. 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), Article 10. https://doi.org/10.1080/00029890.2019.1651168
- Griesemer, M., & Linden, U. (2019). Spectral theory of the Fermi polaron. Ann. Henri Poincaré, 20(6), Article 6. https://doi.org/10.1007/s00023-019-00796-1
- Gyorfi, L., Henze, N., & Walk, H. (2019). The Limit Distribution Of The Maximum Probability Nearest-Neighbour Ball. Journal of Applied Probability, 56(2), Article 2. https://doi.org/10.1017/jpr.2019.37
- Györfi, L., & Walk, H. (2019). Nearest neighbor based conformal prediction. Annales de l’ISUP, 63(2–3), Article 2–3. https://hal.science/hal-03603867
- Hahn, B. N., & Kienle Garrido, M.-L. (2019). An efficient reconstruction approach for a class of dynamic imaging operators. Inverse Problems, 35(9), Article 9. 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), Article 5. 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), Article 3. 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). 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
- 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, Article 131. https://doi.org/10.1016/j.matpur.2019.04.002
- 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), Article 1. 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), Article 23. 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), Article 1. 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), Article 1. 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), Article 28. 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., & Haasdonk, B. (2019). Kernel Methods for Surrogate Modeling (ArXiv No. 1907.10556; Nummer 1907.10556). https://arxiv.org/abs/1907.10556
- Santin, G., Wittwar, D., & Haasdonk, B. (2019). Sparse approximation of regularized kernel interpolation by greedy algorithms.
- 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), Article 1–2. 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), Article 1. 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., & 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.
- Wittwar, D., Santin, G., & Haasdonk, B. (2019). Part II on matrix valued kernels including analysis.
- 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), Article 2. https://doi.org/10.1093/ejcts/ezz027
- Zhang, R., Dippon, J., & Friedel, G. (2019). Refined risk stratification for thoracoscopic lobectomy or segmentectomy. Journal of Thoracic Disease, 11(1), Article 1. https://doi.org/10.21037/jtd.2018.12.44
- 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), Article 6. https://doi.org/10.1177/1094342016684006
- Barth, A., & Kröker, I. (2018). Finite Volume Methods for Hyperbolic Partial Differential Equations with Spatial Noise. In C. Klingenberg & M. Westdickenberg (Hrsg.), Theory, Numerics and Applications of Hyperbolic Problems I (S. 125--135). Springer International Publishing.
- Barth, A., & Stein, A. (2018). A Study of Elliptic Partial Differential Equations with Jump Diffusion Coefficients. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 6(4), Article 4. https://doi.org/10.1137/17M1148888
- Barth, A., & Stein, A. (2018). Approximation and simulation of infinite-dimensional Levy processes. STOCHASTICS AND PARTIAL DIFFERENTIAL EQUATIONS-ANALYSIS AND COMPUTATIONS, 6(2), Article 2. https://doi.org/10.1007/s40072-017-0109-2
- 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
- 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. Proc. ENUMATH 2017.
- 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), Article 1. 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), Article 2. 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), Article 10. 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), Article 5. 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), Article 1. 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), Article 2. 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. (2018). On the mathematical description of time-dependent surface water waves. Jahresber. Dtsch. Math.-Ver., 120(2), Article 2. https://doi.org/10.1365/s13291-017-0173-6
- 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), Article 4. 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), Article 1.
- 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), Article 1. https://doi.org/10.1515/jaa-2018-0007
- 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).
- Escher, J., & Lienstromberg, C. (2018). Travelling waves in dilatant non-Newtonian thin films. J. Differential Equations, 264(3), Article 3. https://doi.org/10.1016/j.jde.2017.10.015
- 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), Article 3. 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). 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
- 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
- Georgiev, V., & Wirth, J. (2018). Zero resonances for localised potentials. Journal of Mathematical Physics, 59(7), Article 7. 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., Stark, D., & Stephan, E. P. (2018). Boundary elements with mesh refinements for the wave equation. Numer. Math., 139(4), Article 4. https://doi.org/10.1007/s00211-018-0954-6
- 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
- Griesemer, M., & Wünsch, A. (2018). On the domain of the Nelson Hamiltonian. J. Math. Phys., 59(4), Article 4. https://doi.org/10.1063/1.5018579
- Griesemer, M., & Linden, U. (2018). Stability of the two-dimensional Fermi polaron. Lett. Math. Phys., 108(8), Article 8. 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), Article 25. 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 No. 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. Math. Nachr., 291, Article 291. https://doi.org/10.1002/mana.201600024
- Holicki, T., & Scherer, C. W. (2018). A Swapping Lemma for Switched Systems. IFAC-PapersOnLine, 51(25), Article 25. 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), Article 2. https://doi.org/10.1007/s10463-016-0595-4
- 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. Calc. Var. Partial Differential Equations, 57(6), Article 6. https://doi.org/10.1007/s00526-018-1426-7
- 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), Article 20. https://doi.org/10.1007/s00021-018-0394-1
- Kovar\’ık, H., Ruszkowski, B., & Weidl, T. (2018). Melas-type bounds for the Heisenberg Laplacian on bounded domains. Journal of Spectral Theory, 8(2), Article 2. 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), Article ja. https://doi.org/10.1002/cnm.3095
- Langer, A. (2018). Overlapping domain decomposition methods for total variation denoising. http://people.ricam.oeaw.ac.at/a.langer/publications/DDfTV.pdf
- 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). 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
- 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. (2018). Equivalent representations of max-stable processes via $\ell^p$-norms. J. Appl. Probab., 55(1), Article 1. https://doi.org/10.1017/jpr.2018.5
- 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), Article 2. 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), Article 2. https://doi.org/10.3150/16-BEJ905
- Oesting, M., & Stein, A. (2018). Spatial modeling of drought events using max-stable processes. Stoch. Env. Res. Risk A., 32(1), Article 1. https://doi.org/10.1007/s00477-017-1406-z
- Oesting, M., & Strokorb, K. (2018). Efficient simulation of Brown-Resnick processes based on variance reduction of Gaussian processes. Adv. in Appl. Probab., 50(4), Article 4. https://doi.org/10.1017/apr.2018.54
- 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), Article 7. 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, Article 3. 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), Article 3. https://doi.org/10.4171/JFG/61