AI RESEARCH
Robust Physics-Guided Diffusion for Full-Waveform Inversion
arXiv CS.AI
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ArXi:2603.16393v1 Announce Type: cross We develop a robust physics-guided diffusion framework for full-waveform inversion that combines a score-based generative prior with likelihood guidance computed through wave-equation simulations. We adopt a transport-based data-consistency potential (Wasserstein-2), incorporating wavefield enhancement via bounded weighting and observation-dependent normalization, thereby improving robustness to amplitude imbalance and time/phase misalignment. On the inference side, we.