Curvature-aware dynamic precision approach for physics-informed neural networks 事件

Curvature-aware dynamic precision approach for physics-informed neural networks arXiv:2606.04736v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have become a promising framework for simulating partial differential equations (PDEs) by embedding physical laws directly into neural network training. However, recent studies show that PINN optimisation is sensitive to numerical precision. Existing implementations commonly use either single precision (FP32), which is computa