8 citations · 14 across the 10 of their papers we have counts for
10 papers
MISNN: Multiple Imputation via Semi-parametric Neural Networks
Zhiqi Bu, Zongyu Dai, Yiliang Zhang +1
Multiple imputation (MI) has been widely applied to missing value problems in biomedical, social and econometric research, in order to avoid improper inference in the downstream da…
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data
Zongyu Dai, Zhiqi Bu, Qi Long
Missing data are ubiquitous in real world applications and, if not adequately handled, may lead to the loss of information and biased findings in downstream analysis. Particularly,…
CEDAR: Communication Efficient Distributed Analysis for Regressions
Changgee Chang, Zhiqi Bu, Qi Long
Electronic health records (EHRs) offer great promises for advancing precision medicine and, at the same time, present significant analytical challenges. Particularly, it is often t…
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation
Kan Chen, Qishuo Yin, Qi Long
Estimating treatment effects is of great importance for many biomedical applications with observational data. Particularly, interpretability of the treatment effects is preferable…
Privacy-Preserving Methods for Vertically Partitioned Incomplete Data
Yi Deng, Xiaoqian Jiang, Qi Long
Distributed health data networks that use information from multiple sources have drawn substantial interest in recent years. However, missing data are prevalent in such networks an…
Grouping effects of sparse CCA models in variable selection
Kefei Liu, Qi Long, Li Shen
The sparse canonical correlation analysis (SCCA) is a bi-multivariate association model that finds sparse linear combinations of two sets of variables that are maximally correlated…