GAC-PINN: Geometry-Adaptive and Constraint-Enhanced Physics-Informed Neural Networks
math.NA, cs.AI, cs.NA
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/lu-group/gpinn
Sources
- Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
- A Lightweight Framework for Trigger-Guided LoRA-Based Self-Adaptation in LLMs
- Spectral Analysis of Hard-Constraint PINNs: The Spatial Modulation Mechanism of Boundary Functions
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