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RISFast and Scalable Likelihood-Free Bayesian Model Updating for Multiple-Measurement Data via Conditional Invertible Neural Network and Posterior Stacking
Publisher: American Society of Civil Engineers
Abstract: AbstractBayesian model updating (BMU) is widely used in structural health monitoring (SHM)
to calibrate model parameters and quantify uncertainties. However, a key challenge
in BMU is the intractability of the likelihood ...