3 papers
stat.ME2026
Mean--Variance Risk-Aware Bayesian Optimal Experimental Design for Nonlinear Models
Wanggang Shen, Xun Huan
We propose a variance-penalized formulation of Bayesian optimal experimental design for nonlinear models that augments the classical expected utility criterion with a penalty on ut…
stat.AP2025
Intelligent data collection for network discrimination in material flow analysis using Bayesian optimal experimental design
Jiankan Liao, Xun Huan, Daniel Cooper
Material flow analyses (MFAs) are powerful tools for highlighting resource efficiency opportunities in supply chains. MFAs are often represented as directed graphs, with nodes deno…
stat.AP2025
Bayesian Model Selection for Network Discrimination and Risk-informed Decision Making in Material Flow Analysis
Jiankan Liao, Xun Huan, Daniel Cooper
Material flow analyses (MFAs) provide insight into supply chain level opportunities for resource efficiency. MFAs can be represented as networks with nodes that represent materials…