3 papers
cs.LG2025
Modeling Non-Ergodic Path Effects Using Conditional Generative Model for Fourier Amplitude Spectra
Maxime Lacour, Pu Ren, Rie Nakata +2
Recent developments in non-ergodic ground-motion models (GMMs) explicitly model systematic spatial variations in source, site, and path effects, reducing standard deviation to 30-4…
physics.geo-ph2025
Advancing data-driven broadband seismic wavefield simulation with multi-conditional diffusion model
Zhengfa Bi, Nori Nakata, Rie Nakata +3
Sparse distributions of seismic sensors and sources pose challenges for subsurface imaging, source characterization, and ground motion modeling. While large-N arrays have shown the…
physics.geo-ph2024
Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling
Pu Ren, Rie Nakata, Maxime Lacour +9
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer fro…