Scale-consistency training, which enforces agreement between global and rescaled sub-domain predictions, enables neural PDE solvers to extrapolate to unseen scale parameters such as Reynolds number or wavenumber.
Neural operators for accelerating scientific simulations and design.Nature Reviews Physics, pages 1–9, 2024
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Scale-Consistent Learning for Partial Differential Equations
Scale-consistency training, which enforces agreement between global and rescaled sub-domain predictions, enables neural PDE solvers to extrapolate to unseen scale parameters such as Reynolds number or wavenumber.