2 citations · 2 across the 9 of their papers we have counts for
11 papers
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…
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…
Inferring Diffusion Structures of Heterogeneous Network Cascade
Yubai Yuan, Siyu Huang, Abdul Basit Adeel
Network cascade refers to diffusion processes in which outcome changes within part of an interconnected population trigger a sequence of changes across the entire network. These ca…
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…
Optimal Transport for Latent Integration with An Application to Heterogeneous Neuronal Activity Data
Yubai Yuan, Babak Shahbaba, Norbert Fortin +3
Detecting dynamic patterns of task-specific responses shared across heterogeneous datasets is an essential and challenging problem in many scientific applications in medical scienc…
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…
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…
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…
Query-augmented Active Metric Learning
Yujia Deng, Yubai Yuan, Haoda Fu +1
In this paper we propose an active metric learning method for clustering with pairwise constraints. The proposed method actively queries the label of informative instance pairs, wh…
High-order joint embedding for multi-level link prediction
Yubai Yuan, Annie Qu
Link prediction infers potential links from observed networks, and is one of the essential problems in network analyses. In contrast to traditional graph representation modeling wh…
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…