4 citations · 7 across the 4 of their papers we have counts for
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stat.ME2019★ 4 cited
Identifying the Influential Inputs for Network Output Variance Using Sparse Polynomial Chaos Expansion
Zhanlin Liu, Ashis G. Banerjee, Youngjun Choe
Sensitivity analysis (SA) is an important aspect of process automation. It often aims to identify the process inputs that influence the process output's variance significantly. Exi…
stat.ME2018★ 3 cited
Data-Driven Sensitivity Indices for Models With Dependent Inputs Using the Polynomial Chaos Expansion
Zhanlin Liu, Youngjun Choe
Uncertainties exist in both physics-based and data-driven models. Variance-based sensitivity analysis characterizes how the variance of a model output is propagated from the model…