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About this paper
Georgios Is. Detorakis
The paper presents DGM, a primer on solving differential equations with neural networks. The network represents the unknown solution and is trained to satisfy the equation and initial and boundary conditions at sampled points. In a one-dimensional heat-equation example, it reports mean absolute error of 0.0029 against the analytic solution, not a comparison with classical solvers.
Summary by alphaXiv.
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