CC-PINN introduces a cross-correlated residual and Fourier-feature MLP to achieve more robust high-contrast reconstructions and faster convergence than standard PINNs in inverse scattering.
Fourier features let networks learn high frequency functions in low dimensional domains
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Beyond Data-Physics Consistency: A Cross-Correlated Physics-Informed Neural Network for Robust Inverse Scattering
CC-PINN introduces a cross-correlated residual and Fourier-feature MLP to achieve more robust high-contrast reconstructions and faster convergence than standard PINNs in inverse scattering.