2026
Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs
ICML 2026poster
We propose Hermite-NGP, a gradient-augmented multi-resolution hash encoding designed to enable fast and accurate computation of spatial derivatives for neural PDE solvers. Unlike existing NGP-based approaches that rely on automatic differentiation or finite differences and suffer from instability or…