18 citations · 33 across the 10 of their papers we have counts for
5 papers · 1 filter
Latent Space-based Stochastic Model Updating
Sangwon Lee, Taro Yaoyama, Masaru Kitahara +1
Model updating of engineering systems inevitably involves handling both aleatory or inherent randomness and epistemic uncertainties or uncertainities arising from a lack of knowled…
Bayesian Structural Model Updating with Multimodal Variational Autoencoder
Tatsuya Itoi, Kazuho Amishiki, Sangwon Lee +1
A novel framework for Bayesian structural model updating is presented in this study. The proposed method utilizes the surrogate unimodal encoders of a multimodal variational autoen…
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…
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…
Emotion Recognition Using Transformers with Masked Learning
Seongjae Min, Junseok Yang, Sangjun Lim +3
In recent years, deep learning has achieved innovative advancements in various fields, including the analysis of human emotions and behaviors. Initiatives such as the Affective Beh…