Adversarial training improves PINNs by using the discriminator to mitigate spectral bias and stiffness, with a new NTK-based framework providing theoretical grounding and a practical algorithm.
Proof.The similarity relation follows directly from K −1/2M K1/2 =K −1/2(KeΓ)K1/2 =K 1/2eΓK1/2 =H.(219) Hence M and H have the same eigenvalues
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When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective
Adversarial training improves PINNs by using the discriminator to mitigate spectral bias and stiffness, with a new NTK-based framework providing theoretical grounding and a practical algorithm.