most citedGenerating Synthetic Systems of Interdependent Critical Infrastructure Networks

15 citations · 19 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022

Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data

Jin-Zhu Yu, Hiba Baroud

Hierarchical Bayesian Poisson regression models (HBPRMs) provide a flexible modeling approach of the relationship between predictors and count response variables. The applications…

cs.LG2022

A Bayesian Approach for the Network Reconstruction of Interdependent Critical Infrastructure Systems from Cascading Failures

MirSaleh Bahavarnia, Hiba Baroud, Yu Wang +1

Analyzing the behavior of complex interdependent networks requires complete information about the network topology and the interdependent links across networks. For many applicatio…

eess.SY2022

Bullwhip Effect of Supply Networks: Joint Impact of Network Structure and Market Demand

Jin-Zhu Yü, Chencheng Cai, Jianxi Gao

The progressive amplification of fluctuations in demand as the demand travels upstream the supply chains is known as the bullwhip effect. We first analytically characterize the bul…

cs.SI2022★ 4 cited

Reconstructing Sparse Multiplex Networks with Application to Covert Networks

Jin-Zhu Yu, Mincheng Wu, Gisela Bichler +2

Network structure provides critical information for understanding the dynamic behavior of networks. However, the complete structure of real-world networks is often unavailable, thu…

physics.soc-ph2021★ 15 cited

Generating Synthetic Systems of Interdependent Critical Infrastructure Networks

Yu Wang, Jin-Zhu Yu, Hiba Baroud

The lack of data on critical infrastructure systems has hindered the research progress in modeling and optimizing the system performance. This work develops a method for generating…