15 citations · 18 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems
Sayyed Mohsen Vazirizade, Ayan Mukhopadhyay, Geoffrey Pettet +3
Principled decision making in emergency response management necessitates the use of statistical models that predict the spatial-temporal likelihood of incident occurrence. These st…
A Review of Incident Prediction, Resource Allocation, and Dispatch Models for Emergency Management
Ayan Mukhopadhyay, Geoffrey Pettet, Sayyed Vazirizade +7
In the last fifty years, researchers have developed statistical, data-driven, analytical, and algorithmic approaches for designing and improving emergency response management (ERM)…