activity
20142017
most citedBayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment

144 citations · 229 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2017144 cited

Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment

Yong Huang, James L. Beck, Hui Li

The focus in this paper is Bayesian system identification based on noisy incomplete modal data where we can impose spatially-sparse stiffness changes when updating a structural mod…

stat.AP2016

Hierarchical Stochastic Model in Bayesian Inference: Theoretical Implications and Efficient Approximation

Stephen Wu, Panagiotis Angelikopoulos, James L. Beck +1

We classify two types of Hierarchical Bayesian Model found in the literature as Hierarchical Prior Model (HPM) and Hierarchical Stochastic Model (HSM). Then, we focus on studying t…

stat.CO2016

Using Approximate Bayesian Computation by Subset Simulation for Efficient Posterior Assessment of Dynamic State-Space Model Classes

Majid K. Vakilzadeh, James L. Beck, Thomas Abrahamsson

Approximate Bayesian Computation (ABC) methods have gained in their popularity over the last decade because they expand the horizon of Bayesian parameter inference methods to the r…

stat.AP201485 cited

Hierarchical sparse Bayesian learning for structural health monitoring with incomplete modal data

Yong Huang, James L. Beck

For civil structures, structural damage due to severe loading events such as earthquakes, or due to long-term environmental degradation, usually occurs in localized areas of a stru…

stat.CO2014

Approximate Bayesian Computation by Subset Simulation

Manuel Chiachio, James L. Beck, Juan Chiachio +1

A new Approximate Bayesian Computation (ABC) algorithm for Bayesian updating of model parameters is proposed in this paper, which combines the ABC principles with the technique of…