AI RESEARCH
A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
arXiv CS.LG
•
ArXi:2604.21411v1 Announce Type: new Standard physics-informed neural networks (PINNs) struggle to simulate highly oscillatory Helmholtz solutions in heterogeneous media because pointwise minimization of second-order PDE residuals is computationally expensive, biased toward smooth solutions, and requires artificial absorbing boundary layers to restrict the solution. To overcome these challenges, we