Auzinger, W., Einramhof, L., Held, K., Kauch, A., Koch, O., Watzenböck, C., & Weinmüller, E. (2025). Efficient adaptive computation of the dynamics of Mott transistors. In T. Simos & C. Tsitouras (Eds.), International Scientific and Practical Symposium “Materials Science and Technology”: MST-IV-2024 (pp. 010001-1-010001–010006). https://doi.org/10.1063/5.0291480

Pavešić, P., Kent, C. A., Herfort, W., & Conner, G. R. (2025). Inverse limits of covering spaces. Fundamenta Mathematicae, 269(2), 99–129. https://doi.org/10.4064/fm231031-9-2

Hohenegger, M., Settanni, G., Weinmüller, E., & Wolde, M. (2024). Numerical treatment of singular ODEs using finite difference and collocation methods. Applied Numerical Mathematics, 205, 184–194. https://doi.org/10.1016/j.apnum.2024.07.002

Gambi, J. M., Phipps, C., Garcia del Pino, M. L., Mosser, J., Weinmüller, E., & Alderete, M. (2024). Deflection of dangerous middle-size LEO debris with autonomous space-based laser brooms via surgical actions. Acta Astronautica, 217, 75–88. https://doi.org/10.1016/j.actaastro.2024.01.021

Brugnano, L., Iavernaro, F., & Weinmüller, E. (2024). Weighted least squares collocation methods. Applied Numerical Mathematics, 203, 113–128. https://doi.org/10.1016/j.apnum.2024.05.017

Djurdjevac, A., Kremp, H., & Perkowski, N. (2024). Weak error analysis for a nonlinear SPDE approximation of the Dean–Kawasaki equation. STOCHASTICS AND PARTIAL DIFFERENTIAL EQUATIONS-ANALYSIS AND COMPUTATIONS. https://doi.org/10.1007/s40072-024-00324-1

Pircher, C., Bachler, M., Ahlström, C., Mayer, C. C., & Hametner, B. (2023). Fit for Duty Assessment of Driver Fatigue based on Statistical Modelling of Cardiovascular Parameters. Simulation Notes Europe, 33(4), 157–166. https://doi.org/10.11128/sne.33.tn.10663

Dareiotis, K., Gerencsér, M., & Lê, K. (2023). Quantifying a convergence theorem of Gyöngy and Krylov. Annals of Applied Probability, 33(3), 2291–2323. https://doi.org/10.1214/22-AAP1867

Charles, F., Massimini, A., & Salvarani, F. (2023). Mathematical and numerical study of a kinetic model describing the evolution of planetary rings. Computers and Mathematics with Applications, 143, 48–56. https://doi.org/10.1016/j.camwa.2023.04.029

Butkovsky, O., Dareiotis, K., & Gerencsér, M. (2023). Optimal Rate of Convergence for Approximations of SPDEs with Nonregular Drift. SIAM Journal on Numerical Analysis, 61(2), 1103–1137. https://doi.org/10.1137/21M1454213

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

Brunner, K., & Hametner, B. (2022). Reviewing Recommender Systems in the Medical Domain. Simulation Notes Europe, 32(4), 203–209. https://doi.org/10.11128/sne.32.tn.10624

Hörandtner, C., Bachler, M., Wassertheurer, S., Breitenecker, F., & Mayer, C. (2022). Pulse Wave Analysis by Quantified Reconstructed Attractors. Simulation Notes Europe, 32(2), 69–78. https://doi.org/10.11128/sne.32.tn.10603

Rößler, M., & Popper, N. (2022). Model Order Reduction of Deterministic Microscopic Models - A Case Study. Simulation Notes Europe, 32(2), 79–84. https://doi.org/10.11128/sne.32.tn.10604

Bicher, M., Wastian, M., Brunmeir, D., & Popper, N. (2022). Review on Monte Carlo Simulation Stopping Rules: How Many Samples Are Really Enough? Simulation Notes Europe, 32(1), 1–8. https://doi.org/10.11128/sne.32.on.10591

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

Hofstätter, H., & Koch, O. (2022). An approximate eigensolver for self-consistent field calculations. Numerical Algorithms, 66, 609–641. https://doi.org/10.1007/s11075-013-9751-6

Pagliari, V., Papafitsoros, K., Raită, B., & Vikelis, A. (2022). Bilevel Training Schemes in Imaging for Total Variation ‒ Type Functionals with Convex Integrands. SIAM Journal on Imaging Sciences, 15(4), 1690–1728. https://doi.org/10.1137/21M1467328

Popper, N., Bicher, M., Breitenecker, F., Glock, B., Hafner, I., Mujica Mota, M., Mušic, G., Rippinger, C., Rössler, M., Schneckenreither, G., Urach, C., Wastian, M., Zauner, G., & Zechmeister, M. (2022). Methods for Integrated Simulation - 10 Concepts to Integrate. Simulation Notes Europe, 32(4), 225–236. https://doi.org/10.11128/sne.32.on.10627

Pruckner, R., & Woracek, H. (2022). A growth estimate for the monodromy matrix of a canonical system. Journal of Spectral Theory, 12(4), 1623–1657. https://doi.org/10.4171/JST/437

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

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

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

Khodadadian, A., Stadlbauer, B., & Heitzinger, C. (2020). Bayesian inversion for nanowire field-effect sensors. Journal of Computational Electronics, 19(1), 147–159. https://doi.org/10.1007/s10825-019-01417-0

Stadlbauer, B., Mitscha-Baude, G., & Heitzinger, C. (2020). Modeling single-molecule stochastic transport for {DNA} exo-sequencing in nanopore sensors. Nanotechnology, 31(7), 075502. https://doi.org/10.1088/1361-6528/ab513e

Taghizadeh, L., Karimi, A., Stadlbauer, B., Weninger, W. J., Kaniusas, E., & Heitzinger, C. (2020). Bayesian inversion for electrical-impedance tomography in medical imaging using the nonlinear Poisson-Boltzmann equation. Computer Methods in Applied Mechanics and Engineering, 365(112959), 112959. https://doi.org/10.1016/j.cma.2020.112959

Stadlbauer, B., Cossettini, A., Morales Escalante, J. A., Pasterk, D., Scarbolo, P., Taghizadeh, L., Heitzinger, C., & Selmi, L. (2019). Bayesian estimation of physical and geometrical parameters for nanocapacitor array biosensors. Journal of Computational Physics, 397, Article 108874. https://doi.org/10.1016/j.jcp.2019.108874

Brown, B. M., Langer, H., & Tretter, C. (2019). Compressed Resolvents and Reduction of Spectral Problems on Star Graphs. Complex Analysis and Operator Theory. https://doi.org/10.1007/s11785-018-0793-6

Rekova, O., Pelzmann, N., Mandl, P., Hoffmann, M., Ecker, H., Körner, A., Bicher, M., & Breitenecker, F. (2019). ARGESIM Benchmark C11 “SCARA Robot”: Comparison of Basic Implementations in EXCEL and MATLAB. SNE Simulation Notes Europe, 29(3), 149–158. https://doi.org/10.11128/sne.29.bne11.10488