2 papers
stat.ML2026
Probabilistic Graphical Model using Graph Neural Networks for Bayesian Inversion of Discrete Structural Component States
Teng Li, Stephen Wu, Yong Huang +2
The health condition of components in civil infrastructures can be described by various discrete states according to their performance degradation. Inferring these states from meas…
stat.AP2026
MCMC with Adaptive Principal-Component Transformation: Rotation-Invariant Universal Samplers for Bayesian Structural System Identification
Xianghao Meng, Yong Huang, James L. Beck +2
Over decades, Markov chain Monte Carlo (MCMC) methods have been widely studied, with a typical application being the quantification of posterior uncertainties in Bayesian system id…