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Biometrics|March 14, 2024
Accounting for network noise in graph-guided Bayesian modeling of structured high-dimensional dataWenrui Li, Changgee Chang, Suprateek Kundu, et al.Biometrics|May 9, 2018
Scalable Bayesian variable selection for structured high-dimensional dataChanggee Chang, Suprateek Kundu, Qi LongBiostatistics (Oxford, England)|January 1, 2019
Bayesian generalized biclustering analysis via adaptive structured shrinkageZiyi Li, Changgee Chang, Suprateek Kundu, et al.Biometrics|May 18, 2026
Knowledge-guided Bayesian biclustering model for omics data with noisy graphsQiyiwen Zhang, Wenrui Li, Suprateek Kundu, et al.Biometrics|November 13, 2025
Bayesian scalar-on-image regression with spatial interactions for modeling Alzheimer's diseaseNilanjana Chakraborty, Qi Long, Suprateek KunduProceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data|February 21, 2022
Graph-guided Bayesian SVM with Adaptive Structured Shrinkage Prior for High-dimensional DataWenli Sun, Changgee Chang, Qi LongJCO Precision Oncology|February 1, 2022
Knowledge-Guided Statistical Learning Methods for Analysis of High-Dimensional -Omics Data in Precision OncologyYize Zhao, Changgee Chang, Qi LongProceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data|May 27, 2020
Bayesian Non-linear Support Vector Machine for High-Dimensional Data with Incorporation of Graph Information on FeaturesWenli Sun, Changgee Chang, Qi LongBriefings in Bioinformatics|December 7, 2023
Robust knowledge-guided biclustering for multi-omics dataQiyiwen Zhang, Changgee Chang, Qi LongBiometrics|October 28, 2022
CEDAR: communication efficient distributed analysis for regressionsChanggee Chang, Zhiqi Bu, Qi LongPageof 139