Applied and Computational Mathematics (ACM)


M. Hutzenthaler, A. Jentzen, T. Kruse and T. A. Nguyen, "Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations" , Journal of Numerical Mathematics, 2022. De Gruyter.
L. Agasthya, A. Bartel, L. Biferale, M. Ehrhardt and F. Toschi, "Lagrangian instabilities in thermal convection with stable temperature profiles" , IMACM preprint 22/10, 2022.
M. Felpel, J. Kienitz and T. A. McWalter, "Effective Markovian projection: application to CMS spread options and mid-curve swaptions" , Quantitative Finance, vol. 22, no. 6, pp. 1169-1192, 2022. Routledge.
M. Ehrhardt, S. Pereselkov, V. Kuz'kin, I. Kaznacheev and P. Rybyanets, "Experimental Observation and Theoretical Analysis of the Low-frequency Source Interferogram and Hologram in Shallow Water" , IMACM preprint 22/08, 2022.
L. Teng, "Gradient boosting-based numerical methods for high dimensional backward stochastic differential equations" , Appl. Math. Comput., vol. 426, pp. 127119, 2022.
M. Muniz, M. Ehrhardt, M. Günther and R. Winkler, "Higher Strong Order Methods for linear {Itô} {SDEs} on matrix {Lie} Groups" , BIT Numer. Math., Jan. 2022. Springer.
N. Nowaczyk, J. Kienitz, S. K. Acar and Q. Liang, "How deep is your model? Network topology selection from a model validation perspective" , JMI, vol. 12 (1), 2022.
M. Hutzenthaler, T. Kruse and T. A. Nguyen, "On the speed of convergence of Picard iterations of BSDEs" , Probability, Uncertainty and Quantitative Risk, vol. 7, no. 2, 2022. American Institute of Mathematical Sciences.
J. Ackermann, T. Kruse and L. Overbeck, "Inhomogeneous affine Volterra processes" , Stochastic Processes and their Applications, vol. 150, pp. 250--279, 2022. North-Holland.
M. E. J.R. Yusupov and D. Matrasulov, "Manakov system on metric graphs: Modeling the reflectionless propagation of vector solitons in networks" , IMACM preprint 22/12, 2022.
J. Jäschke, N. Skrepek and M. Ehrhardt, "Mixed-Dimensional Geometric Coupling of Port-{Hamiltonian} Systems" , IMACM preprint 22/04, 2022.
M. Hutzenthaler, T. Kruse and T. A. Nguyen, "Multilevel Picard approximations for McKean-Vlasov stochastic differential equations" , Journal of Mathematical Analysis and Applications, vol. 507, no. 1, pp. 125761, 2022. Academic Press.
A. Bartel and M. Günther, "Multirate Schemes -- An Answer of Numerical Analysis to a Demand from Applications" in Novel Mathematics Inspired by Industrial Challenges,Michael Günther and Wil Schilders, Eds. Springer, 2022, pp. 5--27.
L. Kapllani and L. Teng, "Multistep schemes for solving backward stochastic differential equations on {GPU}" , JMI, vol. 12, no. 5, 2022.
H. Fatoorehchi and M. Ehrhardt, "Numerical and semi-nume\-rical solutions of a modified Thévenin model for calculating terminal voltage of battery cells" , J. Energy Storage, vol. 45, pp. 103746, 2022. Elsevier.
{. S. Petrov, M. Ehrhardt and {. Y. Trofimov, "On the decomposition of the fundamental solution of the {Helmholtz} equation via solutions of iterative parabolic equations" , Asymptotic Analysis, vol. 126, no. 3-4, pp. 215--228, 2022. IOS Press.
L. Teng and W. Zhao, "High-order combined multi-step scheme for solving forward backward stochastic differential equations" , JSC, vol. 87, no. 81, 2021.
L. Teng, "The Heston model with time-dependent correlation driven by isospectral flows" , Mathematics, vol. 9, no. 9, pp. 934, 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" , Phys. Rev. E, vol. 103, no. 4, pp. 043305, 2021. APS.
M. Hutzenthaler, A. Jentzen and T. Kruse, "Overcoming the curse of dimensionality in the numerical approximation of parabolic partial differential equations with gradient-dependent nonlinearities" , Foundations of Computational Mathematics, pp. 1--62, 2021. Springer US.
J. Ackermann, T. Kruse and M. Urusov, "Optimal trade execution in an order book model with stochastic liquidity parameters" , SIAM Journal on Financial Mathematics, vol. 12, no. 2, pp. 788--822, 2021. Society for Industrial and Applied Mathematics.
M. Hutzenthaler, A. Jentzen, T. Kruse and others, "Multilevel Picard iterations for solving smooth semilinear parabolic heat equations" , Partial Differential Equations and Applications, vol. 2, no. 6, pp. 1--31, 2021. Springer.
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 AG.
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.
A. Clevenhaus, C. Totzeck and M. Ehrhardt, "A Gradient Descent Algorithm for the {Heston} Model" , IMACM preprint 21/32, 2021.

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