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Neural Network-Assisted Refinement of Traditional Schemes for One-Dimensional Scalar Conservation Laws
A clear link is established between conventional numerical methods and neural network approximations for solving one-dimensional scalar conservation laws. The focus is on the construction of an appropriate flux term in the case of convex flux functions for improving the classical schemes. The first
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