P. Putek, A. Bartel, E. J. W. t. Maten and M. Günther, "Shape Optimization of a {PM} Synchronous Machine Under Probabilistic Constraints" in Scientific Computing in Electrical Engineering: SCEE 2018, Taormina, Italy, September 2018 12, 2020, pp. 243--253.

A. Clevenhaus, M. Ehrhardt, M. Günther and D. Ševčovič, "Pricing American options with a non-constant penalty parameter", Journal of Risk and Financial Management, vol. 13, no. 6, pp. 124, 2020. MDPI.

A. Clevenhaus, M. Ehrhardt, M. Günther and D. Ševčovič, "Pricing {American} Options with a Non-Constant Penalty Parameter", J. Risk Fin. Managem., vol. 13, no. 6, pp. 124, Jun. 2020.

M. Hutzenthaler, A. Jentzen, T. Kruse, T. Anh Nguyen and P. Wurstemberger, "Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations", Proceedings of the Royal Society A, vol. 476, no. 2244, pp. 20190630, 2020. The Royal Society Publishing.

C. Beck, F. Hornung, M. Hutzenthaler, A. Jentzen and T. Kruse, "Overcoming the curse of dimensionality in the numerical approximation of Allen--Cahn partial differential equations via truncated full-history recursive multilevel Picard approximations", Journal of Numerical Mathematics, vol. 28, no. 4, pp. 197--222, 2020. De Gruyter.

S. Ankirchner, A. Fromm, T. Kruse and A. Popier, "Optimal position targeting via decoupling fields", The Annals of Applied Probability, vol. 30, no. 2, pp. 644--672, 2020. Institute of Mathematical Statistics.

T. Kruse and P. Strack, "Optimal control of an epidemic through social distancing", Available at SSRN 3581295, 2020.

P. Csomós, M. Ehrhardt and B. Farkas, "Operator splitting for abstract cauchy problems with dynamical boundary condition", arXiv preprint arXiv:2004.13503, 2020.

H. Fatoorehchi and M. Ehrhardt, "Numerical and semi-numerical solutions of a modified Thévenin model with application to the dynamic analysis of electrochemical batteries", 2020.

C. Beck, A. Jentzen and T. Kruse, "Nonlinear Monte Carlo methods with polynomial runtime for high-dimensional iterated nested expectations", arXiv preprint arXiv:2009.13989, 2020.

M. Hutzenthaler and T. Kruse, "Multilevel Picard Approximations of High-Dimensional Semilinear Parabolic Differential Equations with Gradient-Dependent Nonlinearities", SIAM Journal on Numerical Analysis, vol. 58, no. 2, pp. 929--961, 2020. SIAM.

M. Hutzenthaler, A. Jentzen, T. Kruse and T. A. Nguyen, "Multilevel Picard approximations for high-dimensional semilinear second-order PDEs with Lipschitz nonlinearities", arXiv preprint arXiv:2009.02484, 2020.

A. Bartel and M. Günther, "Inter/extrapolation-based multirate schemes: a dynamic-iteration perspective" in Progress in differential-algebraic equations II, 2020, pp. 73--90.

A. Bartel and M. Günther, "Inter/extrapolation-based multirate schemes -- a dynamic-iteration perspective", Reis, Timo and Grundel, Sara and Schöps, Sebastian, Eds. Springer, 2020, pp. 73--90.

J. Backhaus, M. Bolten, O. T. Doganay, M. Ehrhardt, B. Engel, C. Frey, H. Gottschalk, M. Günther, C. Hahn, J. Jäschke, P. Jaksch, K. Klamroth, A. Liefke, D. Luft, L. Mäde, V. Marciniak, M. Reese, J. Schultes, V. Schulz, S. Schmitz, J. Steiner and M. Stiglmayr, "GivEn - Shape Optimization for Gas Turbines in Volatile Energy Networks" in Mathematical MSO for Power Engineering and Management, S. Göttlich and M. Herty and A. Milde, Eds. Springer, 2020.

K. Sabirov, J. Yusupov, M. Ehrhardt and D. Matrasulov, "Transparent boundary conditions for the sine-Gordon equation", 2020.

M. Günther, A. Bartel, B. Jacob and T. Reis, "Dynamic iteration schemes and port-Hamiltonian formulation in coupled DAE circuit simulation", arXiv preprint arXiv:2004.12951, 2020.

J. R. Yusupov, K. K. Sabirov, Q. Asadov, M. Ehrhardt and D. U. Matrasulov, "Dirac particles in transparent quantum graphs: Tunable transport of relativistic quasiparticles in branched structures", Physical Review E, vol. 101, no. 6, pp. 062208, 2020. American Physical Society.

L. Kapllani and L. Teng, "Deep Learning algorithms for solving high dimensional nonlinear Backward Stochastic Differential Equations", arXiv preprint arXiv:2010.01319, 2020.

M. Günther, R. Höllwieser and F. Knechtli, "Constrained hybrid Monte Carlo algorithms for gauge-Higgs models", Computer Physics Communications, vol. 254, pp. 107192, 2020. North-Holland.

M. Günther, R. Höllwiesera and F. Knechtli, "Constrained HMC algorithms for Gauge-Higgs models" in AIP Conference Proceedings, 2020, pp. 290004.

T. Kruse, J. C. Schneider and N. Schweizer, "A toolkit for robust risk assessment using F-divergences", Management Science, 2020. INFORMS Inst. for Operations Res. and the Management Sciences.

J. Kühn, A. Bartel and P. Putek, "A Thermal Extension of Tellinen's Scalar Hysteresis Model" in Scientific Computing in Electrical Engineering SCEE 2018, Springer, Berlin, 2020.

M. Hutzenthaler, A. Jentzen, T. Kruse and T. A. Nguyen, "A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations", SN Partial Differential Equations and Applications, vol. 1, no. 2, pp. 1--34, 2020. Springer International Publishing.

L. Teng, X. Wu, M. Günther and M. Ehrhardt, "A new methodology to create valid time-dependent correlation matrices via isospectral flows", ESAIM: Mathematical Modelling and Numerical Analysis, vol. 54, no. 2, pp. 361--371, Feb. 2020. EDP Sciences.