Aug 15, 2024 · Deep-learning of new first-order finite volume schemes outperforming Godunov and Enquist-Osher for scalar conservation laws.
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Aug 15, 2024 · In this contribution, we study the numerical approximation of scalar conservation laws by computational optimization of the numerical flux ...
Oct 26, 2023 · In this contribution, we study the numerical approximation of scalar conservation laws by computational optimization of the numerical flux ...
Jul 6, 2024 · In this paper we first briefly review the very high order ADER methods for solving hyperbolic conservation laws. ADER methods use high order ...
FVschemesOptim is a Python package that contains the codebase for the paper "Deep learning of first-order nonlinear hyperbolic conservation law solvers".
May 30, 2024 · The proposed method achieves arbitrary high-order accurate in time in a periodic domain and can exactly preserve the discrete mass and original ...
We present GoRINNs: numerical analysis-informed (shallow) neural networks for the solution of inverse problems of non-linear systems of conservation laws.
In this work, we investigate the capabilities of deep neural networks for solving hyperbolic conservation laws with non-convex flux functions.
Deep learning of first-order nonlinear hyperbolic conservation law solvers. Journal of Computational Physics, 511:113114, 2024. ISSN 0021-9991. doi: https ...
In this work, we investigate the capabilities of deep neural networks for solving hyperbolic conservation laws with non-convex flux functions.