Applied and Computational Mathematics (ACM)



2022
M. Muniz, M. Ehrhardt, M. Günther and R. Winkler, "Higher strong order methods for linear Ito SDEs on matrix Lie groups (Jan, 10.1007/s10543-021-00905-9, 2022)", BIT Numerical Mathematics, vol. 62, no. 3, pp. 1093--1093, 2022. SPRINGER VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS.
2021
T. Kossaczká, M. Ehrhardt and M. Günther, "Results in Applied Mathematics", 2021.
L. Teng, "The Heston model with time-dependent correlation driven by isospectral flows", Mathematics, vol. 9, no. 9, pp. 934, 2021.
M. Günther, A. Sandu and A. Zanna, "Symplectic GARK methods for Hamiltonian systems", arXiv preprint arXiv:2103.04110, 2021.
M. Muniz, M. Ehrhardt, M. Günther and R. Winkler, "Stochastic Runge-Kutta--Munthe-Kaas methods in the modelling of perturbed rigid bodies", 2021.
Rosenbrock-Wanner-Type Methods: Theory and Applications. .... Springer, 2021.

ISBN: 978-3030768096

T. Jax, A. Bartel, M. Ehrhardt, M. Günther and G. Steinebach,Rosenbrock--Wanner-Type Methods, 2021.
K. Sabirov, J. Yusupov, M. Aripov, M. Ehrhardt and D. Matrasulov, "Reflectionless propagation of Manakov solitons on a line: A model based on the concept of transparent boundary conditions", Physical Review E, vol. 103, no. 4, pp. 043305, 2021. American Physical Society.
Q. Zhou and Y. Sun, "Explicit high order one-step methods for decoupled forward backward stochastic differential equations", Adv. Appl. Math. Mech, vol. 13, pp. 1293--1317, 2021.
M. Bannenberg, A. Ciccazzo and M. Günther, "Coupling of model order reduction and multirate techniques for coupled dynamical systems", Applied Mathematics Letters, vol. 112, pp. 106780, 2021. Pergamon.
M. Felpel, J. Kienitz and T. A. McWalter, "Effective stochastic volatility: Applications to {ZABR}-type models", Quantitative Finance, vol. 21, no. 5, pp. 837-852, 2021. Routledge.
E. Viviani, L. Di Persio and M. Ehrhardt, "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case", Energies, vol. 14, no. 2, pp. 364, Jan. 2021. MDPI.
E. Viviani, L. Di Persio and M. Ehrhardt,Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case. Energies 2021, 14, 364, 2021.
T. Kossaczk{\'a}, M. Ehrhardt and M. Günther, "Enhanced fifth order {WENO} shock-capturing schemes with deep learning", Res. Appl. Math., vol. 12, pp. 100201, 2021. Elsevier.
T. Kossaczká, M. Ehrhardt and M. Günther, "Enhanced fifth order WENO shock-capturing schemes with deep learning", Results in Applied Mathematics, vol. 12, pp. 100201, 2021. Elsevier.
M. Wandelt, M. Günther and M. Muniz, "Geometric integration on Lie groups using the Cayley transform with focus on lattice QCD", Journal of Computational and Applied Mathematics, vol. 387, pp. 112495, 2021. North-Holland.
J. Ackermann, T. Kruse and M. Urusov, "Càdlàg semimartingale strategies for optimal trade execution in stochastic order book models", Finance and Stochastics, vol. 25, no. 4, pp. 757--810, 2021. Springer Berlin Heidelberg.
J. Backhaus, M. Bolten, O. Tanil Doganay, M. Ehrhardt, B. Engel, C. Frey, H. Gottschalk, M. Günther, C. Hahn, J. Jäschke and others, "GivEn—Shape optimization for gas turbines in volatile energy networks", Mathematical Modeling, Simulation and Optimization for Power Engineering and Management, pp. 71--106, 2021. Springer International Publishing.
L. Teng and W. Zhao, "High-order combined multi-step scheme for solving forward backward stochastic differential equations", JSC, vol. 87, no. 81, 2021.
M. Muniz, M. Ehrhardt, M. Günther and R. Winkler, "Higher Strong Order Methods for It$\backslash$\^{} o SDEs on Matrix Lie Groups", arXiv preprint arXiv:2102.04131, 2021.
D. Simeoni, R. Tripiccione, M. Ehrhardt, C. Alexandrou and S. F. Schifano, "Lattice Kinetic Algorithms for relativistic flows: a unified treatment", University of Cyprus, 2021.
A. Sandu, M. Günther and S. Roberts, "Linearly implicit GARK schemes", Applied Numerical Mathematics, vol. 161, pp. 286--310, 2021. North-Holland.
A. Micheletti, A. Araújo, N. Budko, A. Carpio and M. Ehrhardt,Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics: Effects on health, society, industry, economics and technology, 2021.
M. W. Bannenberg, F. Kasolis, M. Günther and M. Clemens, "Maximum entropy snapshot sampling for reduced basis modelling", COMPEL-The international journal for computation and mathematics in electrical and electronic engineering, vol. 41, no. 3, pp. 954--966, 2021. Emerald Publishing Limited.
J. Ackermann, T. Kruse and M. Urusov, "Càdlàg semimartingale strategies for optimal trade execution in stochastic order book models", Finance and Stochastics, vol. 25, no. 4, pp. 757--810, 2021. Springer Berlin Heidelberg.

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