133 citations · 173 across the 4 of their papers we have counts for
5 papers
Recovering compressed images for automatic crack segmentation using generative models
Yong Huang, Haoyu Zhang, Hui Li +1
In a structural health monitoring (SHM) system that uses digital cameras to monitor cracks of structural surfaces, techniques for reliable and effective data compression are essent…
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…
Langevin Diffusion for Population Based Sampling with an Application in Bayesian Inference for Pharmacodynamics
Georgios Arampatzis, Daniel Wälchli, Panagiotis Angelikopoulos +3
We propose an algorithm for the efficient and robust sampling of the posterior probability distribution in Bayesian inference problems. The algorithm combines the local search capa…
Robust Bayesian compressive sensing with data loss recovery for structural health monitoring signals
Yong Huang, James L. Beck, Stephen Wu +1
The application of compressive sensing (CS) to structural health monitoring is an emerging research topic. The basic idea in CS is to use a specially-designed wireless sensor to sa…
Robust Bayesian compressive sensing for signals in structural health monitoring
Yong Huang, James L. Beck, Stephen Wu +1
In structural health monitoring (SHM) systems, massive amounts of data are often generated that need data compression techniques to reduce the cost of signal transfer and storage.…