3 papers
stat.ML2026
Decomposition for Bayesian Networks: Local and Parallel Inference
Pei Heng, Xinyi Hu, Yi Sun
Probabilistic inference in high-dimensional Bayesian networks is difficult because exact manipulation of the joint distribution scales exponentially with network size. We propose a…
stat.ME2026
Revisiting Madigan and Mosurski: Collapsibility via Minimal Separators
Pei Heng, Shiyuan He, Yi Sun +1
Collapsibility provides a principled approach for dimension reduction in contingency tables and graphical models. Madigan and Mosurski (1990) pioneered the study of minimal collaps…
stat.ML2026
Structural Dimension Reduction in Bayesian Networks
Pei Heng, Yi Sun, Jianhua Guo
This work introduces a novel technique, named structural dimension reduction, to collapse a Bayesian network onto a minimum and localized one while ensuring that probabilistic infe…