Ruibin Xi — accepted AI-conference papers

2025

A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity

Yufei Huang, Changhu Wang, Junjie Tang, Weichi Wu, Ruibin Xi

ICML 2025poster

Traditional network inference methods, such as Gaussian Graphical Models, which are built on continuity and homogeneity, face challenges when modeling discrete data and heterogeneous frameworks. Furthermore, under high-dimensionality, the parameter estimation of such models can be hindered by the no…

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2022

Estimating graphical models for count data with applications to single-cell gene network

Feiyi Xiao, Junjie Tang, Huaying Fang, Ruibin Xi

NeurIPS 2022accept

Graphical models such as Gaussian graphical models have been widely applied for direct interaction inference in many different areas. In many modern applications, such as single-cell RNA sequencing (scRNA-seq) studies, the observed data are counts and often contain many small counts. Traditional gr…

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