A discontinuity-aware PINN with adaptive Fourier features, DyT-plus-spline KAN activations, and learned local viscosity captures shocks with errors between 0.9% and 5% on benchmark PDEs and airfoil flows.
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Discontinuity-aware KAN-based physics-informed neural networks
A discontinuity-aware PINN with adaptive Fourier features, DyT-plus-spline KAN activations, and learned local viscosity captures shocks with errors between 0.9% and 5% on benchmark PDEs and airfoil flows.