When Does Frequency Decomposition Benefit Physics-Informed Neural Networks? A Preliminary Ablation Study
This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.
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 (PINNs) build the governing equations directly into training, but suffer from spect…
Read the full story at arXiv cs.LG ↗
Timeline · 1 report
- 2026-08-27 04:00 · arXiv cs.LG
When Does Frequency Decomposition Benefit Physics-Informed Neural Networks? A Preliminary Ablation Study