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Xi-Lai Liang

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#machine learning Preprint Sep 2026

A Computational Comparison of Fourier Spectral Differentiation and Spatial Automatic Differentiation in Periodic Physics-Informed Neural Networks

Fourier spectral differentiation provides substantially lower training time and memory usage than spatial AD while retaining comparable solution error, at the cost of requiring a uniform structured spatial grid.

Xi-Lai Liang, Zhao-Bin Zhang · 0 citations