extreme-learning-machine

This paper proposes a Frequency Shift Physics-Informed Extreme Learning Machine (FS-PIELM) that uses an additive weight initialization mechanism to overcome spectral bias in solving high-frequency PDEs. The method achieves up to five orders of magnitude improvement over existing PIELM variants on benchmark problems.