Gongjun Xu

31 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-4023-5413

Department of Statistics, University of Michigan

Publications

• Statistical inference for covariate-adjusted and interpretable generalized latent factor model with application to testing fairness — The Annals of Applied Statistics 2026
• High-dimensional factor analysis for network-linked data — Biometrika 2025
• Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
• Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Statistical Inference for Noisy Incomplete Binary Matrix — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• High-Dimensional Inference for Generalized Linear Models with Hidden Confounding — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Survival Analysis via Ordinary Differential Equations — Journal of the American Statistical Association 2023
• A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis — Journal of the American Statistical Association 2023
• Yunxiao Chen and Gongjun Xu's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2023
• Efficient Estimation for Censored Quantile Regression — Journal of the American Statistical Association 2023
• Joint latent space models for network data with high-dimensional node variables — Biometrika 2022
• Partial-mastery cognitive diagnosis models — The Annals of Applied Statistics 2021
• On the phase transition of Wilks’ phenomenon — Biometrika 2021
• Transformed Dynamic Quantile Regression on Censored Data — Journal of the American Statistical Association 2021
• Asymptotically independent U-statistics in high-dimensional testing — The Annals of Statistics 2021
• A Regularization-Based Adaptive Test for High-Dimensional GLMs — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
• Debiased Inference on Treatment Effect in a High-Dimensional Model — Journal of the American Statistical Association 2020
• Partial identifiability of restricted latent class models — The Annals of Statistics 2020
• Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models — Journal of Machine Learning Research 2019 (name-matched, not ORCID-linked)
• Identifying Latent Structures in Restricted Latent Class Models — Journal of the American Statistical Association 2018
• Estimation and Inference of Quantile Regression for Survival Data Under Biased Sampling — Journal of the American Statistical Association 2017
• Rare-event analysis for extremal eigenvalues of white Wishart matrices — The Annals of Statistics 2017
• Identifiability of restricted latent class models with binary responses — The Annals of Statistics 2017
• Joint Scale-Change Models for Recurrent Events and Failure Time — Journal of the American Statistical Association 2017
• An adaptive two-sample test for high-dimensional means — Biometrika 2016
• Statistical Analysis ofQ-Matrix Based Diagnostic Classification Models — Journal of the American Statistical Association 2015
• Some asymptotic results of Gaussian random fields with varying mean functions and the associated processes — The Annals of Statistics 2012
• Identifiability and Inference for Generalized Latent Factor Models — Journal of the American Statistical Association
• Hyperbolic Network Latent Space Model with Learnable Curvature — Journal of the American Statistical Association
• A General Latent Embedding Approach for Modeling Non-uniform High-dimensional Sparse Hypergraphs with Multiplicity — Journal of the American Statistical Association (name-matched, not ORCID-linked)
• Accounting for Measurement Bias: A New Framework for Reliable Country Ranking in Large-Scale Educational Assessments — Journal of the American Statistical Association