jinzhuyu
Assistant Professor in Civil Engineering and Industrial, Manufacturing, and Systems Engineering at UT Arlington.
UT ArlingtonArlington, Texas, USA
Pinned Repositories
AGS_for_HBPRM
Code to implement the approximate Gibbs sampler for efficient inference of the hierarchical Bayesian model for grouped count data. The performance of the proposed sampler is compared against that of the start-of-the-art algorithm, the No-U-Turn-Sampler (NUTS) used by default in Stan.
demo_repo_for_data_science_course
ICOSSAR2021-NetworkResilienceAssessment
Code for the ICOSSAR 2021 paper titled Comparing Topology-based and Flow-based Resilience Assessment of Interdependent Infrastructure Networks
intro-net-sci
materials for a few lectures on the course: introduction to network science
multiplex_recon
Code for the paper "Reconstructuring Sparse Multiplex Networks With Application to Covert Networks"
network_reconstruction
reconstruct network topology from steady states of the dynamical equation
power_restore_patterns
A GUI designed using tkinter to enable users to draw power restoration plots given the location and duration
Rstan_code_HBKM
SBM-for-inter-nets
Code for the paper: Modeling Uncertain and Dynamic Interdependencies of Infrastructure Systems Using Stochastic Block Models (https://asmedigitalcollection.asme.org/risk/article/6/2/020906/1074939/Modeling-Uncertain-and-Dynamic-Interdependencies)
jinzhuyu's Repositories
jinzhuyu/ICOSSAR2021-NetworkResilienceAssessment
Code for the ICOSSAR 2021 paper titled Comparing Topology-based and Flow-based Resilience Assessment of Interdependent Infrastructure Networks
jinzhuyu/multiplex_recon
Code for the paper "Reconstructuring Sparse Multiplex Networks With Application to Covert Networks"
jinzhuyu/network_reconstruction
reconstruct network topology from steady states of the dynamical equation
jinzhuyu/AGS_for_HBPRM
Code to implement the approximate Gibbs sampler for efficient inference of the hierarchical Bayesian model for grouped count data. The performance of the proposed sampler is compared against that of the start-of-the-art algorithm, the No-U-Turn-Sampler (NUTS) used by default in Stan.
jinzhuyu/demo_repo_for_data_science_course
jinzhuyu/intro-net-sci
materials for a few lectures on the course: introduction to network science
jinzhuyu/power_restore_patterns
A GUI designed using tkinter to enable users to draw power restoration plots given the location and duration
jinzhuyu/Rstan_code_HBKM
jinzhuyu/SBM-for-inter-nets
Code for the paper: Modeling Uncertain and Dynamic Interdependencies of Infrastructure Systems Using Stochastic Block Models (https://asmedigitalcollection.asme.org/risk/article/6/2/020906/1074939/Modeling-Uncertain-and-Dynamic-Interdependencies)
jinzhuyu/Scale_Mobility
jinzhuyu/ScrapeWeatherDataFromDarksky
Scrap power outage data and related weather data from different sources
jinzhuyu/stoch_program_inter_net