Bergische Universität Wuppertal Fachbereich Mathematik und Naturwissenschaften Angewandte Mathematik - Numerische Analysis (AMNA)

People Research Publications Teaching

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Summary

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References

• T. Kossaczká, M. Ehrhardt and M. Günther, Deep FDM: Enhanced finite difference methods by deep learning, Preprint 23/06, April 2023.
• T. Kossaczká, M. Ehrhardt and M. Günther, A neural network enhanced weighted essentially non-oscillatory method for nonlinear degenerate parabolic equations, Physics of Fluids, Vol. 34, Issue 2, (2022), 026604. DOI: 10.1063/5.0078397 (open access)
• T. Kossaczká, M. Ehrhardt and M. Günther, Enhanced fifth order WENO Shock-Capturing Schemes with Deep Learning, Results in Applied Mathematics (2021), 100201. DOI: 10.1016/j.rinam.2021.100201 (open access).
• T. Kossaczká, M. Ehrhardt and M. Günther, A Deep Smoothness WENO Method with Applications in Option Pricing, in: M. Ehrhardt and M. Günther (eds.), Progress in Industrial Mathematics at ECMI 2021, The European Consortium for Mathematics in Industry, Springer, 2022, pp 417-423. DOI: 10.1007/978-3-031-11818-0_54.

Talks related to the Project

• M. Ehrhardt, Deep Smoothness WENO Method with Applications in Finance MMEI 2021 conference, Smolenice, Slovakia, September 17, 2021.
• M. Ehrhardt, Enhanced fifth order WENO Shock-Capturing Schemes with Deep Learning COST Action, Seminar of WP 5, 2021.