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20182025
most citedDe-confounding causal inference using latent multiple-mediator pathways

2 citations · 2 across the 9 of their papers we have counts for

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7 papers · 1 filter

stat.ME2025

Distributional Treatment Effect Transportability across Heterogeneous Sites

Borna Bateni, Yubai Yuan, Qi Xu +1

We study distributional transportability of treatment effects in a ``cross-site, one-armed target" design, where both treated and control units are observed in a source site, but o…

stat.ME2025

Scalable Sample-to-Population Estimation of Hyperbolic Space Models for Hypergraphs

Cornelius Fritz, Yubai Yuan, Michael Schweinberger

Hypergraphs are useful mathematical representations of overlapping and nested subsets of interacting units, including groups of genes or brain regions, economic cartels, political…

stat.ME2025

Double machine learning to estimate the effects of multiple treatments and their interactions

Qingyan Xiang, Yubai Yuan, Dongyuan Song +4

Causal inference literature has extensively focused on binary treatments, with relatively fewer methods developed for multi-valued treatments. In particular, methods for multiple s…

stat.ME2024

Individualized Dynamic Mediation Analysis Using Latent Factor Models

Yijiao Zhang, Yubai Yuan, Yuexia Zhang +2

Mediation analysis plays a crucial role in causal inference as it can investigate the pathways through which treatment influences outcome. Most existing mediation analysis assumes…

stat.ME2023★ 2 cited

De-confounding causal inference using latent multiple-mediator pathways

Yubai Yuan, Annie Qu

Causal effect estimation from observational data is one of the essential problems in causal inference. However, most estimation methods rely on the strong assumption that all confo…

stat.ME2023

Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling

Qi Xu, Yubai Yuan, Junhui Wang +1

Crowdsourcing has emerged as an alternative solution for collecting large scale labels. However, the majority of recruited workers are not domain experts, so their contributed labe…

stat.ME2018

Community Detection with Dependent Connectivity

Yubai Yuan, Annie Qu

In network analysis, within-community members are more likely to be connected than between-community members, which is reflected in that the edges within a community are intercorre…