Neural tangent kernel from neural reparameterization modulates sensitivity and wave tangent kernels to produce spectral filtering, wavenumber modulation, and frequency bias that improve NeurFWI convergence.
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A Green-integral neural solver enforces wave physics via nonlocal integral constraints and FFT acceleration to solve the Helmholtz equation more efficiently than standard PINNs on heterogeneous seismic benchmarks.
citing papers explorer
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Deciphering Neural Reparameterized Full-Waveform Inversion with Neural Sensitivity Kernel and Wave Tangent Kernel
Neural tangent kernel from neural reparameterization modulates sensitivity and wave tangent kernels to produce spectral filtering, wavenumber modulation, and frequency bias that improve NeurFWI convergence.
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A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
A Green-integral neural solver enforces wave physics via nonlocal integral constraints and FFT acceleration to solve the Helmholtz equation more efficiently than standard PINNs on heterogeneous seismic benchmarks.