math.NA · 2026-09-29 · No. 128

Numerical Analysis, 2026-09-29.

1 new papers in math.NA. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    GAC-PINN: Geometry-Adaptive and Constraint-Enhanced Physics-Informed Neural Networks

    Yanxin Zhang, Yong Zhang, Houbiao Li

    math.NA · cs.AI

    For systems with steep gradients, sharp interfaces, or severe spatio-temporal coupling, Physics-informed neural networks (PINNs) suffer from spectral bias, geometric inflexibility, and boundary constraint conflicts, which undermine accuracy and convergence. To overcome these issues, we propose a geometry-adaptive and constraint-enhanced PINN (GAC-PINN). The framework comprises four components: a gradient-driven adaptive grid mapping (AGM) for...

    arxiv.org/abs/2609.35196 · PDF

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