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.
Geophysics , volume=
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Introduces a staged pretrain-to-alignment workflow for geophysical AI that improves relative geologic time estimation across global field surveys despite limited labels and domain gaps.
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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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Pretrain-to-alignment learning paradigm to improve geophysical AI applicability under scarce field labels and synthetic-to-field gaps: A case study of relative geologic time estimation in global shelf-edge clinothems
Introduces a staged pretrain-to-alignment workflow for geophysical AI that improves relative geologic time estimation across global field surveys despite limited labels and domain gaps.