Rieder, A. (2025). A P-Version of Convolution Quadrature in Wave Propagation. SIAM Journal on Numerical Analysis, 63(4), 1729–1756. https://doi.org/10.1137/24M1642524

Neunteufel, M., Schöberl, J., & Sturm, K. (2023). Numerical shape optimization of the Canham-Helfrich-Evans bending energy. Journal of Computational Physics, 488, Article 112218. https://doi.org/10.1016/j.jcp.2023.112218

Faustmann, M., Stephan, E. P., & Wörgötter, D. (2023). Two-level error estimation for the integral fractional Laplacian. Computational Methods in Applied Mathematics, 23(3), 603–621. https://doi.org/10.1515/cmam-2022-0195

Angleitner, N., Faustmann, M., & Melenk, J. M. (2023). Exponential meshes and H-matrices. Computers and Mathematics with Applications, 130, 21–40. https://doi.org/10.1016/j.camwa.2022.11.011

Di Fratta, G., Jüngel, A., Praetorius, D., & Slastikov, V. (2023). Spin-diffusion model for micromagnetics in the limit of long times. Journal of Differential Equations, 343, 467–494. https://doi.org/10.1016/j.jde.2022.10.012

Bernkopf, M., & Melenk, J. M. (2023). Optimal convergence rates in L² for a first order system least squares finite element method. ESAIM-MATHEMATICAL MODELLING AND NUMERICAL ANALYSIS, 57(1), 107–141. https://doi.org/10.1051/m2an/2022026

Amad, A. A. S., Ledger, P. D., Betcke, T., & Praetorius, D. (2022). Benchmark computations for the polarization tensor characterization of small conducting objects. Applied Mathematical Modelling, 111, 94–107. https://doi.org/10.1016/j.apm.2022.06.024

Faustmann, M., Melenk, J. M., & Parvizi, M. (2022). 𝘏-matrix approximability of inverses of FEM matrices for the time-harmonic Maxwell equations. Advances in Computational Mathematics, 48(5), Article 59. https://doi.org/10.1007/s10444-022-09965-z

Gangl, P., & Sturm, K. (2022). Automated computation of topological derivatives with application to nonlinear elasticity and reaction–diffusion problems. Computer Methods in Applied Mechanics and Engineering, 398, Article 115288. https://doi.org/10.1016/j.cma.2022.115288

Di Fratta, G., Monteil, A., & Slastikov, V. (2022). Symmetry Properties of Minimizers of a Perturbed Dirichlet Energy with a Boundary Penalization. SIAM Journal on Mathematical Analysis, 54(3), 3636–3653. https://doi.org/10.1137/21M143011X

Kovacs, A., Exl, L., Kornell, A., Fischbacher, J., Hovorka, M., Gusenbauer, M., Breth, L., Oezelt, H., Praetorius, D., Süss, D., & Schrefl, T. (2022). Magnetostatics and micromagnetics with physics informed neural networks. Journal of Magnetism and Magnetic Materials, 548, Article 168951. https://doi.org/10.1016/j.jmmm.2021.168951

Faustmann, M., Melenk, J. M., & Parvizi, M. (2022). Caccioppoli-type estimates and H-matrix approximations to inverses for FEM-BEM couplings. Numerische Mathematik, 150, 849–892. https://doi.org/10.1007/s00211-021-01261-0

Auer, F. K., Auzinger, W., Burkotová, J., Rachůnková, I., & Weinmüller, E. B. (2022). On nonlinear singular BVPs with nonsmooth data. Part 2: Convergence of collocation methods. Applied Numerical Mathematics, 171, 149–175. https://doi.org/10.1016/j.apnum.2021.08.016

Auzinger, W., Burdeos, K., Fallahpour, M., Koch, O., Mendoza, R., & Weinmüller, E. (2022). A numerical continuation method for parameter-dependent boundary value problems using bvpsuite 2.0. Journal of Numerical Analysis, Industrial and Applied Mechanics (JNAIAM), 16(1–2), 1–13.

Auzinger, W., Dubois, J., Held, K., Hofstätter, H., Jawecki, T., Kauch, A., Koch, O., Kropielnicka, K., Singh, P., & Watzenböck, C. (2022). Efficient Magnus-type integrators for solar energy conversion in Hubbard models. Journal of Computational Mathematics and Data Science, 2(100018), 100018. https://doi.org/10.1016/j.jcmds.2021.100018

Becker, R., Brunner, M., Innerberger, M., Melenk, J. M., & Praetorius, D. (2022). Rate-optimal goal-oriented adaptive finite element method for semilinear elliptic PDEs. Computers & Mathematics with Applications, 118, 18–35. https://doi.org/10.1016/j.camwa.2022.05.008

Becker, R., Innerberger, M., & Praetorius, D. (2022). Adaptive FEM for parameter-errors in elliptic linear-quadratic parameter estimation problems. SIAM Journal on Numerical Analysis, 60(3), 1450–1471. https://doi.org/10.1137/21m1458077

Davoli, E., Di Fratta, G., Praetorius, D., & Ruggeri, M. (2022). Micromagnetics of thin films in the presence of Dzyaloshinskii-Moriya interaction. Mathematical Models and Methods in Applied Sciences, 32(05), 911–939. https://doi.org/10.1142/s0218202522500208

Gambi, J. M., García del Pino, M. L., Mosser, J., & Weinmüller, E. (2022). Trailing formations of lightweight spacecrafts to deflect NEAs by means of laser ablation. Acta Astronautica, 190, 241–250. https://doi.org/10.1016/j.actaastro.2021.10.006

Gantner, G., & Praetorius, D. (2022). Adaptive BEM for elliptic PDE systems, Part I: Abstract framework for weakly-singular integral equations. Applicable Analysis, 101(6), 2085–2118. https://doi.org/10.1080/00036811.2020.1800651

Gantner, G., & Praetorius, D. (2022). Adaptive BEM for elliptic PDE systems, Part II: Isogeometric analysis with hierarchical B-splines for weakly-singular integral equations. Computers & Mathematics with Applications, 117, 74–96. https://doi.org/10.1016/j.camwa.2022.04.006

Gantner, G., & Praetorius, D. (2022). Plain convergence of adaptive algorithms without exploiting reliability and efficiency. IMA Journal of Numerical Analysis, 42(2), 1434–1453. https://doi.org/10.1093/imanum/drab010

Mauser, N. J., Pfeiler, C.-M., Praetorius, D., & Ruggeri, M. (2022). Unconditional well-posedness and IMEX improvement of a family of predictor-corrector methods in micromagnetics. Applied Numerical Mathematics, 180, 33–54. https://doi.org/10.1016/j.apnum.2022.05.008

Oezelt, H., Qu, L., Kovacs, A., Fischbacher, J., Gusenbauer, M., Beigelbeck, R., Praetorius, D., Masao, Y., Shoji, T., Kato, A., Chantrell, R., Winklhofer, M., Zimanyi, G., & Schrefl, T. (2022). Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal. Npj Computational Materials, 8(35). https://doi.org/10.1038/s41524-022-00719-5

Gambi, J. M., Garcia del Pino, M. L., Mosser, J., & Weinmüller, E. (2021). Computational Modeling and Simulation to Increase Laser Shooting Accuracy of Autonomous LEO Trackers. Photonics, 8(2), Article 55. https://doi.org/10.3390/photonics8020055

Achleitner, F., Kuehn, C., Melenk, J. M., & Rieder, A. (2021). Metastable Speeds in the Fractional Allen-Cahn Equation. Applied Mathematics and Computation, 408(126329), 126329. https://doi.org/10.1016/j.amc.2021.126329

Amodio, P., Arnold, A., Levitina, T., Settanni, G., & Weinmüller, E. B. (2021). On the Abramov approach for the approximation of whispering gallery modes in prolate spheroids. Applied Mathematics and Computation, 409(125599), 125599. https://doi.org/10.1016/j.amc.2020.125599

Angleitner, N., Faustmann, M., & Melenk, J. M. (2021). Approximating inverse FEM matrices on non-uniform meshes with H-matrices. Calcolo, 58(31). https://doi.org/10.1007/s10092-021-00413-w

Auzinger, W., Březinová, I., Grosz, A., Hofstätter, H., Koch, O., & Sato, T. (2021). Efficient adaptive exponential time integrators for nonlinear Schrödinger equations with nonlocal potential. Journal of Computational Mathematics and Data Science, 1(100014), 100014. https://doi.org/10.1016/j.jcmds.2021.100014

Auzinger, W., Hofstätter, H., Koch, O., & Quell, M. (2021). Adaptive Time Propagation for Time-Dependent Schrödinger Equations. International Journal of Applied and Computational Mathematics, 7, Article 6. https://doi.org/10.1007/s40819-020-00937-9

Baumann, P., & Sturm, K. (2021). Adjoint-based methods to compute higher-order topological derivatives with an application to elasticity. Engineering Computations, 39(1), 60–114. https://doi.org/10.1108/ec-07-2021-0407

Becker, R., Innerberger, M., & Praetorius, D. (2021). Optimal convergence rates for goal-oriented FEM with quadratic goal functional. Computational Methods in Applied Mathematics, 21(2), 267–288. https://doi.org/10.1515/cmam-2020-0044

Bespalov, A., Praetorius, D., & Ruggeri, M. (2021). Convergence and rate optimality of adaptive multilevel stochastic Galerkin FEM. IMA Journal of Numerical Analysis, 42(3), 2190–2213. https://doi.org/10.1093/imanum/drab036

Bespalov, A., Praetorius, D., & Ruggeri, M. (2021). Two-level a posteriori error estimation for adaptive multilevel stochastic Galerkin FEM. SIAM/ASA Journal on Uncertainty Quantification, 9(3), 1184–1216. https://doi.org/10.1137/20m1342586

Bohn, J., & Feischl, M. (2021). Recurrent neural networks as optimal mesh refinement strategies. Computers and Mathematics with Applications, 97, 61–76. https://doi.org/10.1016/j.camwa.2021.05.018

Dick, J., & Feischl, M. (2021). A quasi-Monte Carlo data compression algorithm for machine learning. Journal of Complexity, 67(101587), 101587. https://doi.org/10.1016/j.jco.2021.101587

Edalatzadeh, M. S., Kalise, D., Morris, K. A., & Sturm, K. (2021). Optimal Actuator Design for the Euler-Bernoulli Vibration Model Based on LQR Performance and Shape Calculus. IEEE Control Systems Letters, 6, 1334–1339. https://doi.org/10.1109/lcsys.2021.3093215

Faustmann, M., Melenk, J. M., & Parvizi, M. (2021). On the stability of Scott-Zhang type operators and application to multilevel preconditioning in fractional diffusion. ESAIM: Mathematical Modelling and Numerical Analysis, 55(2), 595–625. https://doi.org/10.1051/m2an/2020079

Faustmann, M., Melenk, J. M., & Praetorius, D. (2021). Quasi-optimal convergence rate for an adaptive method for the integral fractional Laplacian. Mathematics of Computation, 90(330), 1557–1587. https://doi.org/10.1090/mcom/3603

Feischl, M., & Scaglioni, A. (2021). Convergence of adaptive stochastic collocation with finite elements. Computers and Mathematics with Applications, 98, 139–156. https://doi.org/10.1016/j.camwa.2021.07.001

Gangl, P., & Sturm, K. (2021). Topological derivative for PDEs on surfaces. SIAM Journal on Control and Optimization, 60(1), 81–103. https://doi.org/10.1137/20m1339040

Gantner, G., Haberl, A., Praetorius, D., & Schimanko, S. (2021). Rate optimality of adaptive finite element methods with respect to the overall computational costs. Mathematics of Computation, 90(331), 2011–2040. https://doi.org/10.1090/mcom/3654

Haberl, A., Praetorius, D., Schimanko, S., & Vohralík, M. (2021). Convergence and quasi-optimal cost of adaptive algorithms for nonlinear operators including iterative linearization and algebraic solver. Numerische Mathematik, 147(3), 679–725. https://doi.org/10.1007/s00211-021-01176-w

Heid, P., Praetorius, D., & Wihler, T. P. (2021). Energy contraction and optimal convergence of adaptive iterative linearized finite element methods. Computational Methods in Applied Mathematics, 21(2), 407–422. https://doi.org/10.1515/cmam-2021-0025

Innerberger, M., & Praetorius, D. (2021). Instance-optimal goal-oriented adaptivity. Computational Methods in Applied Mathematics, 21(1), 109–126. https://doi.org/10.1515/cmam-2019-0115

Jawecki, T. (2021). A study of defect-based error estimates for the Krylov approximation of phi-functions. Numerical Algorithms, 90(1), 323–361. https://doi.org/10.1007/s11075-021-01190-x

Kurz, S., Pauly, D., Praetorius, D., Repin, S., & Sebastian, D. (2021). Functional a posteriori error estimates for boundary element methods. Numerische Mathematik, 147(4), 937–966. https://doi.org/10.1007/s00211-021-01188-6

Markus Melenk, J., & Rieder, A. (2021). hp-FEM for the fractional heat equation. IMA Journal of Numerical Analysis, 41(1), 412–454. https://doi.org/10.1093/imanum/drz054

Melenk, J. M., & Rieder, A. (2021). On superconvergence of Runge-Kutta convolution quadrature for the wave equation. Numerische Mathematik, 147(1), 157–188. https://doi.org/10.1007/s00211-020-01161-9

Melenk, J. M., & Sauter, S. A. (2021). wavenumber-explicit hp-FEM analysis for Maxwell’s equations with transparent boundary conditions. Foundations of Computational Mathematics, 21(1), 125–241. https://doi.org/10.1007/s10208-020-09452-1

Rieder, A., Sayas, F.-J., & Melenk, J. M. (2021). Runge-Kutta approximation for C₀-semigroups in the graph norm with applications to time domain boundary integral equations. Partial Differential Equations and Applications, 1(6), Article 49. https://doi.org/10.1007/s42985-020-00051-x

Erath, C., Gantner, G., & Praetorius, D. (2020). Optimal convergence behavior of adaptive FEM driven by simple (h − h/2)-type error estimators. Computers and Mathematics with Applications, 79(3), 623–642. https://doi.org/10.1016/j.camwa.2019.07.014

Feischl, M., & Schwab, Ch. (2020). Exponential convergence in H1 of hp-FEM for Gevrey regularity with isotropic singularities. Numerische Mathematik, 144, 323–346. https://doi.org/10.1007/s00211-019-01085-z

Albuquerque, Y. F., Laurain, A., & Sturm, K. (2020). A shape optimization approach for electrical impedance tomography with pointwise measurements. Inverse Problems, 36(9), 095006. https://doi.org/10.1088/1361-6420/ab9f87

Amodio, P., Budd, C. J., Koch, O., Rottschäfer, V., Settanni, G., & Weinmüller, E. (2020). Near critical, self-similar, blow-up solutions of the generalised Korteweg-de Vries equation: asymptotics and computations. Physica D: Nonlinear Phenomena, 401(132179), 132179. https://doi.org/10.1016/j.physd.2019.132179

Di Fratta, G., Innerberger, M., & Praetorius, D. (2020). Weak-strong uniqueness for the Landau-Lifshitz-Gilbert equation in micromagnetics. Nonlinear Analysis: Real World Applications, 55, Article 103122. https://doi.org/10.1016/j.nonrwa.2020.103122

Di Fratta, G., Pfeiler, C.-M., Praetorius, D., Ruggeri, M., & Stiftner, B. (2020). Linear second-order IMEX-type integrator for the (eddy current) Landau-Lifshitz-Gilbert equation. IMA Journal of Numerical Analysis, 40(4), 2802–2838. https://doi.org/10.1093/imanum/drz046

Feischl, M., & Peterseim, D. (2020). Sparse Compression of Expected Solution Operators. SIAM Journal on Numerical Analysis, 58(6), 3144–3164. https://doi.org/10.1137/20m132571x

Feischl, M., & Schwab, Ch. (2020). Exponential convergence in H1 of hp-FEM for Gevrey regularity with isotropic singularities. Numerische Mathematik, 144(2), 323–346. https://doi.org/10.1007/s00211-019-01085-z

Führer, T., & Praetorius, D. (2020). A short note on plain convergence of adaptive least-squares finite element methods. Computers and Mathematics with Applications, 80(6), 1619–1632. https://doi.org/10.1016/j.camwa.2020.07.022

Gangl, P., & Sturm, K. (2020). A simplified derivation technique of topological derivatives for quasi-linear transmission problems. ESAIM: Control, Optimisation and Calculus of Variations, 26, 106. https://doi.org/10.1051/cocv/2020035

Gangl, P., & Sturm, K. (2020). Asymptotic analysis and topological derivative for 3D quasi-linear magnetostatics. ESAIM: Control, Optimisation and Calculus of Variations, 55, 853–875. https://doi.org/10.1051/m2an/2020060

Gangl, P., Sturm, K., Neunteufel, M., & Schöberl, J. (2020). Fully and semi-automated shape differentiation in NGSolve. Structural and Multidisciplinary Optimization, 63(3), 1579–1607. https://doi.org/10.1007/s00158-020-02742-w

Gantner, G., & Praetorius, D. (2020). Adaptive IGAFEM with optimal convergence rates: T-splines. Computer Aided Geometric Design, 81(101906). https://doi.org/10.1016/j.cagd.2020.101906

Gantner, G., Praetorius, D., & Schimanko, S. (2020). Adaptive isogeometric boundary element methods with local smoothness control. Mathematical Models and Methods in Applied Sciences, 30(02), 261–307. https://doi.org/10.1142/s0218202520500074

Innerberger, M., Worm, P., Prauhart, P., & Kauch, A. (2020). Electron-light interaction in nonequilibrium -- exact diagonalization for time dependent Hubbard Hamiltonians. European Physical Journal Plus, 135(922). https://doi.org/10.1140/epjp/s13360-020-00919-2

Jawecki, T., Auzinger, W., & Koch, O. (2020). Computable upper error bounds for Krylov approximations to matrix exponentials and associated phi-functions. BIT Numerical Mathematics, 60(1), 157–197. https://doi.org/10.1007/s10543-019-00771-6

Karkulik, M., Melenk, J. M., & Rieder, A. (2020). Stable decompositions of hp-BEM spaces and an optimal Schwarz preconditioner for the hypersingular integral operator in 3D. ESAIM: Mathematical Modelling and Numerical Analysis, 54(1), 145–180. https://doi.org/10.1051/m2an/2019041

Khodadadian, A., Noii, N., Parvizi, M., Abbaszadeh, M., Wick, T., & Heitzinger, C. (2020). A Bayesian estimation method for variational phase-field fracture problems. Computational Mechanics, 66(4), 827–849. https://doi.org/10.1007/s00466-020-01876-4

Khodadadian, A., Parvizi, M., & Heitzinger, C. (2020). An adaptive multilevel Monte-Carlo algorithm for the stochastic drift-diffusion-Poisson system. Computer Methods in Applied Mechanics and Engineering, 368(113163), 113163. https://doi.org/10.1016/j.cma.2020.113163

Mascotto, L., Melenk, J. M., Perugia, I., & Rieder, A. (2020). FEM-BEM mortar coupling for the Helmholtz equation in three dimensions. Computers and Mathematics with Applications, 80(11), 2351–2378. https://doi.org/10.1016/j.camwa.2020.04.014

Melenk, J. M., & Rojik, C. (2020). On commuting p-version projection-based interpolation on tretrahedra. Mathematics of Computation, 89(321), 45–87. https://doi.org/10.1090/mcom/3454

Melenk, J. M., Sauter, S. A., & Torres, C. (2020). Wave number-Explicit Analysis for Galerkin Discretizations of Lossy Helmholtz Problems. SIAM Journal on Numerical Analysis, 58(4), 2119–2143. https://doi.org/10.1137/19m1253952

Pfeiler, C.-M., & Praetorius, D. (2020). Dörfler marking with minimal cardinality is a linear complexity problem. Mathematics of Computation, 89(326), 2735–2752. https://doi.org/10.1090/mcom/3553

Pfeiler, C.-M., Ruggeri, M., Stiftner, B., Exl, L., Hochsteger, M., Hrkac, G., Schöberl, J., Mauser, N. J., & Praetorius, D. (2020). Computational micromagnetics with Commics. Computer Physics Communications, 248, Article 106965. https://doi.org/10.1016/j.cpc.2019.106965

Praetorius, D., Ruggeri, M., & Stephan, E. P. (2020). The saturation assumption yields optimal convergence of two-level adaptive BEM. Applied Numerical Mathematics, 152, 105–124. https://doi.org/10.1016/j.apnum.2020.01.014

Schattauer, C., Linhart, L., Fabian, T., Jawecki, T., Auzinger, W., & Libisch, F. (2020). Graphene quantum dot states near defects. Physical Review B, 102(155430). https://doi.org/10.1103/physrevb.102.155430

Sturm, K. (2020). First-order differentiability properties of a class of equality constrained optimal value functions with applications to shape optimization. Journal of Nonsmooth Analysis and Optimization. https://doi.org/10.46298/jnsao-2020-6034

Sturm, K. (2020). Topological sensitivities via a Lagrangian approach for semilinear problems. Nonlinearity, 33(9), 4310–4337. https://doi.org/10.1088/1361-6544/ab86cb

Gambi, J. M., Garcia del Pinto, M. L., Mosser, J., & Weinmüller, E. (2019). Numerical Approach for the Computation of Preliminary Post-Newtonian Corrections for Laser Links in Space. International Journal of Aerospace Engineering, 2019, 1–7. https://doi.org/10.1155/2019/3723018

Auzinger, W., Březinová, I., Hofstätter, H., Koch, O., & Quell, M. (2019). Practical Splitting Methods for the Adaptive Integration of Nonlinear Evolution Equations. Part II: Comparison of Local Error Estimation and Step-Selection Strategies for Nonlinear Schrödinger and Wave Equations. Computer Physics Communications, 234, 55–71. https://doi.org/10.1016/j.cpc.2018.08.003

Auzinger, W., Hofstätter, H., & Koch, O. (2019). Non-existence of generalized splitting methods with positive coefficients of order higher than four. Applied Mathematics Letters, 97, 48–52. https://doi.org/10.1016/j.aml.2019.05.017

Auzinger, W., Hofstätter, H., & Koch, O. (2019). Symmetrized local error estimators for time-reversible one-step methods in nonlinear evolution equations. Journal of Computational and Applied Mathematics, 356, 339–357. https://doi.org/10.1016/j.cam.2019.02.011

Auzinger, W., Hofstätter, H., Koch, O., Kropielnicka, K., & Singh, P. (2019). Time adaptive Zassenhaus splittings for the Schrödinger equation in the semiclassical regime. Applied Mathematics and Computation, 362, Article 124550. https://doi.org/10.1016/j.amc.2019.06.064

Auzinger, W., Hofstätter, H., Koch, O., Quell, M., & Thalhammer, M. (2019). A Posteriori Error Estimation for Magnus-Type Integrators. ESAIM: Mathematical Modelling and Numerical Analysis, 53(1), 197–218. https://doi.org/10.1051/m2an/2018050

Banjai, L., Melenk, J. M., Nochetto, R. H., Otárola, E., Salgado, A. J., & Schwab, C. (2019). Tensor FEM for spectral fractional diffusion. Foundations of Computational Mathematics, 19(4), 901–962. https://doi.org/10.1007/s10208-018-9402-3

Bespalov, A., Betcke, T., Haberl, A., & Praetorius, D. (2019). Adaptive BEM with optimal convergence rates for the Helmholtz equation. Computer Methods in Applied Mechanics and Engineering, 346, 260–287. https://doi.org/10.1016/j.cma.2018.12.006

Bespalov, A., Praetorius, D., Rocchi, L., & Ruggeri, M. (2019). Convergence of adaptive stochastic Galerkin FEM. SIAM Journal on Numerical Analysis, 57(5), 2359–2382. https://doi.org/10.1137/18m1229560

Bespalov, A., Praetorius, D., Rocchi, L., & Ruggeri, M. (2019). Goal-oriented error estimation and adaptivity for elliptic PDEs with parametric or uncertain inputs. Computer Methods in Applied Mechanics and Engineering, 345, 951–982. https://doi.org/10.1016/j.cma.2018.10.041

Betcke, T., Haberl, A., & Praetorius, D. (2019). Adaptive boundary element methods for the computation of the electrostatic capacity on complex polyhedra. Journal of Computational Physics, 397, Article 108837. https://doi.org/10.1016/j.jcp.2019.07.036

Di Fratta, G., Führer, T., Gantner, G., & Praetorius, D. (2019). Adaptive Uzawa algorithm for the Stokes equation. ESAIM: Mathematical Modelling and Numerical Analysis, 53(6), 1841–1870. https://doi.org/10.1051/m2an/2019039

Dick, J., Feischl, M., & Schwab, C. (2019). Improved efficiency of a multi-index FEM for computational uncertainty quantification. SIAM Journal on Numerical Analysis, 57(4), 1744–1769. https://doi.org/10.1137/18m1193700

Erath, C., & Praetorius, D. (2019). Adaptive vertex-centered finite volume methods for general second-order linear elliptic PDEs. IMA Journal of Numerical Analysis, 39(2), 983–1008. https://doi.org/10.1093/imanum/dry006

Erath, C., & Praetorius, D. (2019). Optimal adaptivity for the SUPG finite element method. Computer Methods in Applied Mechanics and Engineering, 353, 308–327. https://doi.org/10.1016/j.cma.2019.05.028

Feischl, M. (2019). Optimality of a standard adaptive finite element method for the Stokes problem. SIAM Journal on Numerical Analysis, 57(3), 1124–1157. https://doi.org/10.1137/17m1153170

Führer, T., Gantner, G., Praetorius, D., & Schimanko, S. (2019). Optimal additive Schwarz preconditioning for adaptive 2D IGA boundary element methods. Computer Methods in Applied Mechanics and Engineering, 351, 571–598. https://doi.org/10.1016/j.cma.2019.03.038

Führer, T., Haberl, A., Praetorius, D., & Schimanko, S. (2019). Adaptive BEM with inexact PCG solver yields almost optimal computational costs. Numerische Mathematik, 141(4), 967–1008. https://doi.org/10.1007/s00211-018-1011-1

Hrkac, G., Pfeiler, C.-M., Praetorius, D., Ruggeri, M., Segatti, A., & Stiftner, B. (2019). Convergent tangent plane integrators for the simulation of chiral magnetic skyrmion dynamics. Advances in Computational Mathematics, 45(3), 1329–1368. https://doi.org/10.1007/s10444-019-09667-z

Karkulik, M., & Melenk, J. M. (2019). H-matrix approximability of inverses of discretizations of the fractional Laplacian. Advances in Computational Mathematics, 45(5–6), 2893–2919. https://doi.org/10.1007/s10444-019-09718-5

Kraus, J., Pfeiler, C.-M., Praetorius, D., Ruggeri, M., & Stiftner, B. (2019). Iterative solution and preconditioning for the tangent plane scheme in computational micromagnetics. Journal of Computational Physics, 398, Article 108866. https://doi.org/10.1016/j.jcp.2019.108866

Tung, M. M., & Weinmüller, E. B. (2019). Acoustic Metamaterial Models on the (2+1)D Schwarzschild Plane. Journal of Computational and Applied Mathematics, 346, 162–170. https://doi.org/10.1016/j.cam.2018.07.009

Zehetgruber, F. K. (2025, July 14). Iterative Approximation of Solution Operators for PDEs with Neural Networks. ICOSAHOM 2025, Montréal, Canada.

Sturm, K. (2025, July 7). A multimaterial topology optimisation approach to Dirichlet control with piecewise constant functions. European Solid Mechanics Conference (ESMC 2025), Lyon, France.

Faustmann, M. (2024, November 7). Quantum Computing - ein Quantensprung?. TUforMath 2024, Austria.

Brunner, M., Becker, R., Innerberger, M., Melenk, J. M., & Praetorius, D. (2023, September 4). Rate-optimal goal-oriented adaptive FEM for semilinear elliptic PDEs. European Conference on Numerical Mathematics and Advanced Applications (ENUMATH 2023), Lissabon, Portugal.

Baumann, P., Mazari, I., & Sturm, K. (2023, August 24). Topology optimisation with general dilatations via the topological state derivative. 10th International Congress on Industrial and Applied Mathematics : ICIAM 2023 Tokyo, Tokyo, Japan.

Rieder, A. (2023, July 26). A p-version of convolution quadrature in wave propagation. POWER 2023, Torino, Italy.

Faustmann, M., Marcati, C., Melenk, J. M., & Schwab, C. (2023, June 29). Exponential convergence of hp-FEM for the integral fractional Laplacian. 29th Biennial Conference on Numerical Analysis, Glasgow, United Kingdom of Great Britain and Northern Ireland (the).

Streitberger, J., Brunner, M., Heid, P., Innerberger, M., Miraci, A., & Praetorius, D. (2023, April 27). Adaptive FEM for linear elliptic PDEs: optimal complexity. Austrian Numerical Analysis Day 2023, Wien, Austria.

Faustmann, M., & Rieder, A. (2023, March 8). FEM-BEM Coupling in Fractional Diffusion. Nonlocal Equations: Analysis and Numerics, Germany.

Faustmann, M., Marcati, C., Melenk, J. M., & Schwab, Ch. (2022, September 15). Weighted analytic regularity and hp-FEM for the integral fractional Laplacian. Chemnitz FE Symposium 2022, Herrsching, Germany.

Faustmann, M., Marcati, C., Melenk, J. M., & Schwab, Ch. (2022, August 31). Weighted analytic regularity for the integral fractional Laplacian in polygons. Computational Methods in Applied Mathematics 2022, Wien, Austria.

Auzinger, W., Grosz, A., Hofstätter, H., & Koch, O. (2022). Adaptive Time Propagation of the MCTDHF Equations. SDIDE 2022 - 6th Workshop on Stability and Discretization Issues in Differential Equations, Budapest, Hungary.

Auzinger, W., Held, K., Kauch, A., Watzenböck, C., & Koch, O. (2022). Adaptive Magnus-type integrators for the simulation of solar cells. Austrian Numerical Analysis Day 2022, Linz, Austria.

Bahr, B. H., Faustmann, M., Melenk, J. M., & Praetorius, D. (2022). Adaptive FEM for fractional diffusion. ESI Workshop “Adaptivity, High Dimensionality and Randomness,” Wien, Austria.

Becker, R., Brunner, M., Innerberger, M., Melenk, J. M., & Praetorius, D. (2022). Goal-oriented adaptive finite element method for semilinear elliptic PDEs. RMMM 2022 - Reliable Methods of Mathematical Modeling, Lausanne, Switzerland.

Becker, R., Gantner, G., Innerberger, M., & Praetorius, D. (2022). Goal-oriented adaptive finite element methods with optimal computational complexity. Mathematisches Kolloquium, TH Aachen, Austria.

Becker, R., Innerberger, M., & Praetorius, D. (2022). Adaptive FEM for parameter-errors in elliptic linear-quadratic parameter estimation problems. RMMM 2022 - Reliable Methods of Mathematical Modeling, Lausanne, Switzerland.

Brunner, M., Gantner, G., Innerberger, M., & Praetorius, D. (2022). Adaptive FEM with quasi-optimal cost for nonlinear PDEs. GATIPOR Workshop 2022 on Interplay of discretization and algebraic solvers: a posteriori error estimates and adaptivity, Paris, France.

Faustmann, M., Marcati, C., Melenk, J. M., & Schwab, C. (2022). Analytic Regularity and hp-FEM for the Integral Fractional Laplacian. 19th European Finite Element Fair, Espo, Finland.

Praetorius, D. (2022). On optimal computational costs of AFEM. CC2LX - Workshop on Finite Element Methods and Adaptivity, TU Wien, Austria.

Auer, F., Auzinger, W., Burkotova, J., Fallahpour, M., Rachunkova, I., & Weinmüller, E. (2021). Numerical Solution of Singular ODEs with Nonsmooth Data. ICNAAM 2021 - 19th International Conference on Numerical Analysis and Applied Mathematics, Rhodos, Greece.

Auzinger, W., Jawecki, T., Koch, O., Pukach, P., Stolyarchuk, R., & Weinmüller, E. (2021). Some Aspects on [numerical] Stability of Evolution Equations of Stiff Type; Use of Computer Algebra. In 2021 IEEE XVIIth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH). MEMSTECH 2021, Polyana, Ukraine. IEEE Ukraine Section. https://doi.org/10.1109/memstech53091.2021.9468055

Auzinger, W., Obelovska, K., Dronyuk, I., Pelekh, K., & Stolyarchuk, R. (2021). A Continuous Model for States in CSMA/CA-Based Wireless Local Networks Derived from State Transition Diagrams. In M. Saraswat, S. Roy, C. Chowdhury, & A. H. Gandomi (Eds.), Proceedings of International Conference on Data Science and Applications (pp. 571–579). Lecture Notes in Networks and Systems, Springer. https://doi.org/10.1007/978-981-16-5348-3_45

Banjai, L., Melenk, J. M., & Schwab, C. (2021). hp-FEM for the spectral fractional Laplacian in polygons. world congress of computational mechanics 2020, Paris, France.

Becker, R., Gantner, G., Innerberger, M., & Praetorius, D. (2021). Goal-oriented adaptive finite element methods with optimal computational complexity. Recent Advances in the Numerical Approximation of Partial Differential Equations (RANAPDE 2021), Milan (online), Italy.

Becker, R., Innerberger, M., & Praetorius, D. (2021). Optimal convergence rates for goal-oriented FEM with quadratic goal functional. Online Conference “14th World Congress in Computational Mechanics and ECCOMAS Congress (WCCM-ECCOMAS 2020),” Paris, online, France.

Bespalov, A., Praetorius, D., & Ruggeri, M. (2021). Rate optimality of an adaptive multilevel stochastic Galerkin finite element method. Congress of the Italian Society of Industrial and Applied Mathematics (SIMAI 2020+2021), Parma, Italy.

Faustmann, M., Karkulik, M., Melenk, J. M., & Praetorius, D. (2021). Finite Element Method for Fractional Diffusion - Recent Results. DMV-ÖMG Jahrestagung 2021, virtuelle Tagung - Zoom / Passau, Germany.

Gambi, J. M., Garcia del Pino, M. L., Mosser, J., & Weinmüller, E. (2021). Computational procedure to increase the shooting accuracy of swarms od space-based laser trackers to deflect NEOs by means of ablation. 7th IAA PLANETARY DEFENSE CONFERENCE 2021, Wien, Austria.

Kvasnicka, D., & Roda, G. (2021). Big Data on the Vienna Scientific Cluster. In Austrian-Slovenian HPC Meeting 2021 – ASHPC21 (p. 37). IZUM.

Pukach, P., Slipchuk, A., Auzinger, W., Stolyarchuk, R., Pukach, Y., Kunynets, A., & Pabyrivska, N. (2021). Asymptotic Method for Studying Mathematical Models of Resonant and Nonresonant Nonlinear Vibrations for Some 1D Moving Bodies. In 2021 IEEE 16th International Conference on the Experience of Designing and Application of CAD Systems (CADSM). CADSM’2021, Lviv, Ukraine. IEEE. https://doi.org/10.1109/cadsm52681.2021.9385221

Weinmüller, E., Gambi, J. M., Garcia del Pino, M. L., & Mosser, J. (2021). Computational Procedure to Increase the Shooting Accuracy of Swarms of Space-based Laser Trackers to Deflect NEOS by Means of Ablation. 7th IAA Planetary Defense, Wien, Austria.

Auzinger, W., Grosz, A., Hofstätter, H., & Koch, O. (2020). Adaptive Exponential Integrators for MCTDHF. In I. Lirkov & S. Margenov (Eds.), Large-Scale Scientific Computing (pp. 557–565). Springer Lecture Notes in Computer Science (LNCS). https://doi.org/10.1007/978-3-030-41032-2_64

Auzinger, W., Kytmanov, A. A., & Tsarev, S. P. (2020). A Study of Anomalies in GPS Time Series via Polynomial Filtering. In 2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT). 15th International Scientific and Technical Conference Computer Science and Information Technologies, Zbarazh-Lviv, Ukraine. IEEE. https://doi.org/10.1109/csit49958.2020.9321909

Auzinger, W., Obelovska, K., & Stolyarchuk, R. (2020). A Modified Gomory-Hu Algorithm with DWDM-Oriented Technology. In I. Lirkov & S. Margenov (Eds.), Large-Scale Scientific Computing 12th International Conference, LSSC 2019 (pp. 547–554). Springer Lecture Notes in Computer Science (LNCS). https://doi.org/10.1007/978-3-030-41032-2_63

Auzinger, W., Obelovska, K., & Stolyarchuk, R. (2020). A Revised Gomory-Hu Algorithm Taking Account of Physical Unavailability of Network Channels. In P. Gaj, W. Gumiński, & A. Kwiecień (Eds.), Computer Networks (pp. 3–13). Springer International Publishing. https://doi.org/10.1007/978-3-030-50719-0_1

Auzinger, W., Stolyarchuk, R., Pelekh, Y., Kozar, O., Mentynskyi, S., & Ihnatyshyn, M. (2020). The Studying of Hydrogen Diffusion Non-Stationary Processes Near a Crack in the Field of Heterogeneous Mechanical Tensions for the Encapsulated MEMS Devices. In 2020 IEEE XVIth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH). IEEE Xplore. https://doi.org/10.1109/memstech49584.2020.9109464

Banjai, L., Melenk, J. M., & Schwab, C. (2020). hp-FEM for the spectral fractional Laplacian. Recent progress in nonlocal modelling, analysis, and computation, Bejing, China.

Bespalov, A., Praetorius, D., & Ruggeri, M. (2020). Error estimation and adaptive algorithms for multilevel stochastic Galerkin FEM. 20th Biennial Computational Techniques and Applications Conference (CTAC 2020), Sydney, Australia.

Bespalov, A., Praetorius, D., & Ruggeri, M. (2020). Error estimation and adaptive algorithms for multilevel stochastic Galerkin FEM. Chemnitz Finite Element Symposium 2020 (online edition), Chemnitz, Germany.

Di Fratta, G., Innerberger, M., Praetorius, D., Pfeiler, C.-M., & Ruggeri, M. (2020). Chiral magnetic skyrmions and computational micromagnetism. 19th GAMM Seminar on Microstructures, Freiburg, Germany.

Di Fratta, G., Innerberger, M., Praetorius, D., Pfeiler, C.-M., & Ruggeri, M. (2020). Chiral magnetic skyrmions and computational micromagnetism. Universität Würzburg, Oberseminar des Lehrstuhls für Mathematik in den Naturwissenschaften, Würzburg, Germany.

Faustmann, M., Karkulik, M., Melenk, J. M., Parvizi, M., & Praetorius, D. (2020). The Fractional Laplacian - Adaptive FEM, Preconditioning and Local Errors. USM Seminar, Valparaiso (online), Chile.

Faustmann, M., Melenk, J. M., & Karkulik, M. (2020). Local convergence of the FEM for the integral fractional Laplacian. 4th Conference on Numerical Methods for Fractional-Derivative Problems, Peking (online), China.

Kurz, S., Pauly, D., Praetorius, D., Repin, S., & Sebastian, D. (2020). Functional a posteriori error estimates for boundary element methods. In Boundary Element Methods (pp. 342–346).

Roda, G., Linauer, L., & Kvasnicka, D. (2020). Apache Spark is here to stay. In Austrian HPC Meeting 2020 (AHPC2020) - Booklet of abstracts (pp. 41–42). https://doi.org/10.15479/AT:ISTA:7474

Tsarev, S., Kytmanov, A., & Auzinger, W. (2020). Discrete orthogonal polynomials: anomalies of time series and boundary effects of polynomial filters. Workshop at Novosibirsk State University, Novosibirsk, Russian Federation (the).

Auinger, B., Hollaus, K., Leumüller, M., Nannen, L., & Wess, M. (2019). Complex Scaled Infinite Elements for Electromagnetic Problems in Open Domains. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 518–519). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Auzinger, W., Burkotova, J., Rachunkova, I., & Wenin, V. (2019). Numerical exploration of impulsive boundary value problems. Workshop on Numerical Solution of Integral and Differential Equations (NSIDE 2019), Gdansk, Poland.

Auzinger, W., Grosz, A., Hofstätter, H., & Koch, O. (2019). Efficient adaptive time integrators for high-dimensional Schrödinger equations. Workshop on Numerical Solution of Integral and Differential Equations (NSIDE 2019), Gdansk, Poland.

Auzinger, W., Hofstätter, H., & Koch, O. (2019). Precise local error control for symmetric one-step schemes applied to nonlinear evolution equations. SciCADE 2019, International Conference on Scientific Computation and Differential Equations, Innsbruck, Austria.

Auzinger, W., Hofstätter, H., & Koch, O. (2019). An algorithm for computing coefficients of words in expressions envolving exponentials and its application to the construction of exponential integrators. In Computer Algebra in Scientific Computing (pp. 197–214). Springer Lecture Notes in Computer Science (LNCS).

Auzinger, W., Hofstätter, H., Jawecki, T., Koch, O., Kropielnicka, K., & Singh, P. (2019). Adaptive exponential methods. SciCADE 2019, International Conference on Scientific Computation and Differential Equations, Innsbruck, Austria.

Auzinger, W., Hofstätter, H., Koch, O., Kropielnicka, K., & Singh, P. (2019). Time adaptive Zassenhaus splittings for the Schrödinger equation in the semiclassical regime. ParNum 2019, Dubrovnik, Croatia.

Auzinger, W., Jawecki, T., & Koch, O. (2019). Computable upper error bounds for Krylov subspace approximations to matrix exponentials. SciCADE 2019, International Conference on Scientific Computation and Differential Equations, Innsbruck, Austria.

Auzinger, W., Stolyarchuk, R., & Stoliarchuk, R. (2019). Strongly damped Stiff Oscillator under External Force: A Case Study. In Proceedings of the 9-th International Youth Science Forum “Litteris et Artibus” (pp. 22–28).

Banjai, L., Melenk, J. M., & Schwab, C. (2019). hp-FEM for the spectral fractional Laplacian in polygons. oberwolfach conference on innovative discretization techniques, oberwolfach, Germany.

Bernkopf, M., & Melenk, J. M. (2019). Analysis of the hp-version of a first order system least squares method for the Helmholtz equations. In T. Apel, U. Langer, A. Meyer, & O. Steinbach (Eds.), Advanced Finite Element Methods with Applications  Selected Papers from the 30th Chemnitz Finite Element Symposium (pp. 57–84). Springer LNCSE. https://doi.org/10.1007/978-3-030-14244-5_4

Bespalov, A., Praetorius, D., Rocchi, L., & Ruggeri, M. (2019). Convergence of adaptive stochastic Galerkin FEM for elliptic parametric PDEs. MAFELAP 2019 - The Mathematics of Finite Elements and Applications, Uxbridge, United Kingdom of Great Britain and Northern Ireland (the).

Blankrot, B., & Heitzinger, C. (2019). Efficiently optimizing inclusion rotation angle for maximal power flow. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 480–481). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Dronyuk, I., Fedevych, O., Stolyarchuk, R., & Auzinger, W. (2019). OMNET++ and Maple software environments for IT Bachelor studies. In E. Shakshuki, A. Yasar, & H. Malik (Eds.), Procedia Computer Science (pp. 654–659). Procedia Computer Science. https://doi.org/10.1016/j.procs.2019.08.093

Faustmann, M. (2019). Wie das Dezimalsystem nach Europa kam. TUforMath, Wien, Austria.

Faustmann, M., Melenk, J. M., & Praetorius, D. (2019). OEMG jahrestagung. OEMG Jahrestagung 2019, Dornbirn, Austria.

Faustmann, M., Melenk, J. M., Parvizi, M., & Praetorius, D. (2019). Optimal adaptivity and preconditioning for the fractional Laplacian. 15th Austrian Numerical Analysis Day, Graz, Austria.

Faustmann, M., Melenk, J. M., Parvizi, M., & Praetorius, D. (2019). Optimal adaptivity and preconditioning for the fractional Laplacian. GAMM 2019, Wien, Austria.

Faustmann, M., Melenk, J. M., Parvizi, M., & Praetorius, D. (2019). Optimal adaptivity and preconditioning for the fractional Laplacian. WONAPDE 2019 - Sixth Chilean Workshop on Numerical Analysis of Partial Differential Equations, Concepción, Chile.

Führer, T., Haberl, A., Praetorius, D., & Schimanko, S. (2019). Adaptive BEM with inexact PCG solver yields almost optimal computational costs. MAFELAP 2019 - The Mathematics of Finite Elements and Applications, Uxbridge, United Kingdom of Great Britain and Northern Ireland (the).

Führer, T., Praetorius, D., & Schimanko, S. (2019). Adaptive BEM with inexact PCG solver yields almost optimal computational costs. Universität Bayreuth, Bayreuth, Germany, Austria.

Gantner, G., & Praetorius, D. (2019). A posteriori error estimation and convergence of adaptive isogeometric methods. 7th International Conference on Isogeometric Analysis, München, Germany.

Gantner, G., Haberl, A., Praetorius, D., & Schimanko, S. (2019). Rate optimal adaptive FEM with inexact solver for nonlinear operators. WONAPDE 2019 - Sixth Chilean Workshop on Numerical Analysis of Partial Differential Equations, Concepción, Chile.

Gantner, G., Haberlik, D., & Praetorius, D. (2019). Axioms of adaptivity revisited: Optimal adaptive IGAFEM. WONAPDE 2019 - Sixth Chilean Workshop on Numerical Analysis of Partial Differential Equations, Concepción, Chile.

Gantner, G., Haberlik, D., & Praetorius, D. (2019). Optimal adaptivity for isogeometric finite and boundary element methods. Seminar on Numerical Analysis (Inria), Paris, France.

Gantner, G., Praetorius, D., & Schimanko, S. (2019). Rate optimal adaptive FEM with inexact solver for nonlinear operators. BI.discrete - Numerical Analysis in Bielefeld, Bielefeld, Germany.

Gopalakrishnan, J., Schöberl, J., & Wintersteiger, C. (2019). An explicit Mapped Tent Pitching scheme for hyperbolic systems. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 272–273). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Innerberger, M., & Praetorius, D. (2019). Instance-Optimal Goal-Oriented Adaptivity. RMMM 2019 - Reliable Methods of Mathematical Modeling, TU Wien, Austria.

Jawecki, T. (2019). Computable upper error bounds for Krylov subspace approximations to matrix exponentials. Numerical Analysis Group Internal Seminar, Oxford, United Kingdom of Great Britain and Northern Ireland (the).

Jawecki, T. (2019). Performance evaluation of the Magnus-Lanczos method. TU-D Workshop 2019, Langenlois, Austria.

Kapidani, B., & Schöberl, J. (2019). A matrix-free Discontinuous Galerkin method for the time dependent Maxwell equations in open domians. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 432–433). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Kurz, S., Pauly, D., Praetorius, D., Repin, S., & Sebastian, D. (2019). Functional a posteriori error estimates for boundary element methods. 17th workshop on Fast boundary element methods in industrial applications, Söllerhaus, Hirschegg, Austria.

Kurz, S., Pauly, D., Praetorius, D., Repin, S., & Sebastian, D. (2019). Functional a posteriori error estimates for boundary element methods. RMMM 2019 - Reliable Methods of Mathematical Modeling, TU Wien, Austria.

Melenk, J. M. (2019). AFEM for fractional Laplacian. MAFELAP 2019 - The Mathematics of Finite Elements and Applications, Uxbridge, United Kingdom of Great Britain and Northern Ireland (the).

Melenk, J. M. (2019). AFEM for fractional Laplacian. Nonlocal Operators, Edinburgh, United Kingdom of Great Britain and Northern Ireland (the).

Melenk, J. M. (2019). High order least squares for Helmholtz equation. WONAPEDE, Concepcion, Chile.

Melenk, J. M. (2019). hp-FEM for Maxwell’s equation. HOFEIM 2019, Pavia, Italy.

Melenk, J. M. (2019). hp-FEM for fractional Laplacian. GAMM 2019, Wien, Austria.

Melenk, J. M. (2019). hp-FEM for fractional diffusion. MAFELAP 2019 - The Mathematics of Finite Elements and Applications, Uxbridge, United Kingdom of Great Britain and Northern Ireland (the).

Nannen, L., Tichy, K., & Wess, M. (2019). Complex Scaled Infinite Elements for Wave Equations in Heterogeneous Open Systems. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 520–521). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Nytrebych, Z., Ilkiv, V., Malanchuk, O., & Auzinger, W. (2019). Investigation of mathematical model of acoustic wave propagation through relax environment in ultrasound diagnostics problems. In Informatics & Data-Driven Medicine 2019 (pp. 280–289). CEUR-WS.

Pfeiler, C.-M., & Praetorius, D. (2019). Dörfler marking with minimal cardinality is a linear complexity problem. 15th Austrian Numerical Analysis Day, Graz, Austria.

Pfeiler, C.-M., & Praetorius, D. (2019). Dörfler marking with minimal cardinality is a linear complexity problem. DMV-Jahrestagung 2019, KIT Karlsruhe, Germany.

Pfeiler, C.-M., & Praetorius, D. (2019). Dörfler marking with minimal cardinality is a linear complexity problem. RMMM 2019 - Reliable Methods of Mathematical Modeling, TU Wien, Austria.

Pfeiler, C.-M., & Praetorius, D. (2019). Dörfler marking with minimal cardinality is a linear complexity problem. WONAPDE 2019 - Sixth Chilean Workshop on Numerical Analysis of Partial Differential Equations, Concepción, Chile.

Pfeiler, C.-M., Ruggeri, M., Stiftner, B., Exl, L., Hochsteger, M., Hrkac, G., Schöberl, J., Mauser, N. J., & Praetorius, D. (2019). Computational studies of nonlinear skyrmion dynamics. HMM 2019 - 12th International Symposium on Hysteresis Modeling and Micromagnetics, Heraklion, Crete, Greece.

Praetorius, D., Ruggeri, M., & Stephan, E. P. (2019). The saturation assumption yields optimal convergence of two-level adaptive BEM. 17th workshop on Fast boundary element methods in industrial applications, Söllerhaus, Hirschegg, Austria.

Praetorius, D., Schimanko, S., & Gantner, G. (2019). Rate optimal adaptive FEM with inexact solver for nonlinear operators. ENUMATH 2019 - European Numerical Mathematics and Advanced Applications Conference 2019, Egmond aan Zee, Netherlands (the).

Pukach, P., Ilkiv, V., Vovk, M., Slyusarchuk, O., Pukach, Y., Mylyan, Y., & Auzinger, W. (2019). On the mathematical model of nonlinear vibrations of a biologically active rod with consideration of the rheological factor. In Informatics & Data-Driven Medicine 2019 (pp. 30–42). CEUR-WS.

Schimanko, S., Praetorius, D., Führer, T., & Haberl, A. (2019). Adaptive BEM with inexact PCG solver yields almost optimal computational costs. SIAM Conference on Computational Science and Engineering (CSE 2019), Spokane, Washington, United States of America (the).

Taus, M., Zepeda-Núnez, L., Hewett, R. J., & Demanent, L. (2019). L-Sweeps: a scalable parallel preconditioner for the high-frequency Helmholtz equation. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 250–251). Proceedings of the 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation.

Toth, F., Hassanpour Guilvaiee, H., & Kaltenbacher, M. (2019). Efficient Modeling Strategies for Thermoviscous Acoustics. In M. Kaltenbacher, J. M. Melenk, L. Nannen, & F. Toth (Eds.), The 14th International Conference on Mathematical and Numerical Aspects of Wave Propagation (pp. 160–161). Institute of Mechanics and Mechatronics, Faculty of Mechanical and Industrial Engineering, Institute of Analysis and Scientific Computing, Faculty of Mathematics and Geoinformation, TU Wien Wien.

Weinmüller, E. (2019). Analysis of the singular BVPs, linear problem with constant coefficient matrix. Vortrag an University of Philippines, Diliman, Manila, Philippines (the).

Weinmüller, E. (2019). Analysis of the singular BVPs, linear problem with variable coefficient matrix. Vortrag an University of Philippines, Diliman, Manila, Philippines (the).

Weinmüller, E. (2019). Collocation - an efficient tool for solving singular ODEs and DAEs. MNPS 2019, Moskau, Russian Federation (the).

Weinmüller, E. (2019). Error estimation, grid adaptation, Matlab code bvpsuite, applications. Vortrag an University of Philippines, Diliman, Manila, Philippines (the).

Weinmüller, E. (2019). Numerical Treatment of Implicit singular BVPs in ODEs. European Women in Mathematics, Leipzig, Germany.

Weinmüller, E. (2019). Numerical approach by finite differences and collocatuion. Vortrag an University of Philippines, Diliman, Manila, Philippines (the).

Weinmüller, E. (2019). Self-similar, blow-up solutions of the generalized Korteweg-de Vries Equation near criticality. SIAM Conference on Applications of Dynamical Systems, Snowbird, Austria.

Weinmüller, E., Budd, Ch., Koch, O., & Rottschäfer, V. (2019). Blow-up in the generalized Korteweg-de Vries equation. 1st PUC-Bath Workshop on Nonlinear PDEs and Application, Santiago de Chile, Chile.

Weinmüller, E., Budd, Ch., Koch, O., & Rottschäfer, V. (2019). Things that go bang in the night: Short history of blow-up and how to compute it. Tutorial Workshop Geometry, Compatibility and Structure Preservation in computational differential equations, Isaak Newton Institute, Cambridge, United Kingdom of Great Britain and Northern Ireland (the).

Weinmüller, E., Burdeos, K., Fallahpour, M., & Mendoza, R. (2019). Path-following for parameter-dependent boundary value problems in singular ordinary differential equations. 8th SEAMS-UGM 2019, Yogyakarta, Indonesia.

Weinmüller, E., Burkotova, J., & Rachunkova, I. (2019). Collocation for solving BVPs with nonsmooth data. ICNAAM 2019, Rhodos, Greece.

Weinmüller, E., Burkotova, J., & Rachunkova, I. (2019). Convergence of collocation for singular BVPs with nonsmooth data. Workshop on Numerical Solution of Integral and Differential Equations (NSIDE 2019), Gdansk, Poland.