When does frequency decomposition benefit physics-informed neural networks? a preliminary ablation study
Read the original at arxiv.org→arXiv:2608.24940v1 Announce Type: new Abstract: Partial differential equations (PDEs) often have high-frequency and multi-scale features that neural networks struggle to approximate. Physics-Informed Neural Networks...
Original headline: "When Does Frequency Decomposition Benefit Physics-Informed Neural Networks? A Preliminary Ablation Study"
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- Aug 27, 04:00 UTC arXiv cs.LG lead source When Does Frequency Decomposition Benefit Physics-Informed Neural Networks? A Preliminary Ablation Study
- Aug 27, 04:00 UTC arXiv cs.LG Physics-Informed Error Field Learning: A Post-Training Optimization Framework for Physics-Informed Neural Networks