FS-PIELM shifts the mean of Gaussian weights (variance fixed at 1) in PIELM to bound frequency variance and achieve 1-5 orders of magnitude better accuracy on high-frequency PDE benchmarks while retaining single linear solve efficiency.
Two-level random feature methods for elliptic partial differential equations over complex domains.Computer Methods in Applied Mechanics and Engineering, 441:117961, 2025
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Frequency Shift Physics-Informed Extreme Learning Machine for Solving High-Frequency Partial Differential Equations
FS-PIELM shifts the mean of Gaussian weights (variance fixed at 1) in PIELM to bound frequency variance and achieve 1-5 orders of magnitude better accuracy on high-frequency PDE benchmarks while retaining single linear solve efficiency.