most citedSite-Specific Ground Motion Generative Model for Crustal Earthquakes in Japan Based on Generative Adversarial Networks

6 citations · 8 across the 2 of their papers we have counts for

collaborators

2 papers

physics.geo-ph2024★ 6 cited

Site-Specific Ground Motion Generative Model for Crustal Earthquakes in Japan Based on Generative Adversarial Networks

Yuma Matsumoto, Taro Yaoyama, Sangwon Lee +2

We develop a site-specific ground-motion model (GMM) for crustal earthquakes in Japan that can directly model the probability distribution of ground motion acceleration time histor…

stat.AP2024★ 2 cited

Latent Space-Based Likelihood Estimation Using a Single Observation for Bayesian Updating of a Nonlinear Hysteretic Model

Sangwon Lee, Taro Yaoyama, Yuma Matsumoto +2

This study presents a novel approach to quantifying uncertainties in Bayesian model updating, which is effective in sparse or single observations. Conventional uncertainty quantifi…