Similarity of markers identified from cancer gene expression studies: observations from GEO. - Xingjie Shi; Shihao Shen; Jin Liu 011; Jian Huang 003; Yong Zhou; Shuangge Ma (Briefings Bioinform., 2014)

EPS: an empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes. - Jin Liu 011; Xiang Wan; Shuangge Ma; Can Yang 002 (Bioinform., 2016)

IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies. - Mingwei Dai; Jingsi Ming; Mingxuan Cai; Jin Liu 011; Can Yang 002; Xiang Wan; Zongben Xu (Bioinform., 2017)

LLR: a latent low-rank approach to colocalizing genetic risk variants in multiple GWAS. - Jin Liu 011; Xiang Wan; Chaolong Wang; Chao Yang; Xiaowei Zhou 001; Can Yang 002 (Bioinform., 2017)

LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. - Jingsi Ming; Mingwei Dai; Mingxuan Cai; Xiang Wan; Jin Liu 011; Can Yang 002 (Bioinform., 2018)

Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. - Mingwei Dai; Xiang Wan; Hao Peng; Yao Wang 003; Yue Liu; Jin Liu 011; Zongben Xu; Can Yang 002 (Bioinform., 2019)

VIMCO: variational inference for multiple correlated outcomes in genome-wide association studies. - Xingjie Shi; Yuling Jiao; Yi Yang 028; Ching-Yu Cheng; Can Yang 002; Xinyi Lin; Jin Liu 011 (Bioinform., 2019)

CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information. - Can Yang 002; Xiang Wan; Xinyi Lin; Mengjie Chen; Xiang Zhou; Jin Liu 011 (Bioinform., 2019)

Wasserstein-Wasserstein Auto-Encoders. - Shunkang Zhang; Yuan Gao 044; Yuling Jiao; Jin Liu 011; Yang Wang; Can Yang 002 (CoRR, 2019)

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies. - Yi Yang 028; Xingjie Shi; Yuling Jiao; Jian Huang 003; Min Chen; Xiang Zhou; Lei Sun; Xinyi Lin; Can Yang 002; Jin Liu 011 (Bioinform., 2020)

Bayesian weighted Mendelian randomization for causal inference based on summary statistics. - Jia Zhao; Jingsi Ming; Xianghong Hu; Gang Chen; Jin Liu 011; Can Yang 002 (Bioinform., 2020)

A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models. - Jian Huang 003; Yuling Jiao; Lican Kang; Jin Liu 011; Yanyan Liu; Xiliang Lu (CoRR, 2020)

Learning Implicit Generative Models with Theoretical Guarantees. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011 (CoRR, 2020)

Generative Learning With Euler Particle Transport. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2020)

Deep Generative Learning via Euler Particle Transport. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011; Xiliang Lu; Jerry Zhijian Yang (MSML, 2021)

Robust recovery in 1-bit compressive sensing via ℓq-constrained least squares. - Qibin Fan; Cui Jia; Jin Liu 011; Yuan Luo (Signal Process., 2021)

SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes. - Yi Yang 028; Xingjie Shi; Wei Liu; Qiuzhong Zhou; Mai Chan Lau; Jeffrey Chun Tatt Lim; Lei Sun; Cedric Chuan Young Ng; Joe Yeong; Jin Liu 011 (Briefings Bioinform., 2022)

MR-Corr2: a two-sample Mendelian randomization method that accounts for correlated horizontal pleiotropy using correlated instrumental variants. - Qing Cheng; Tingting Qiu; Xiaoran Chai; Baoluo Sun; Yingcun Xia; Xingjie Shi; Jin Liu 011 (Bioinform., 2022)

GSDAR: a fast Newton algorithm for ℓ 0 regularized generalized linear models with statistical guarantee. - Jian Huang 003; Yuling Jiao; Lican Kang; Jin Liu 011; Yanyan Liu; Xiliang Lu (Comput. Stat., 2022)

Invariant and Sufficient Supervised Representation Learning. - Junyu Zhu; Xu Liao; Changshi Li; Yuling Jiao; Jin Liu 011; Xiliang Lu (IJCNN, 2023)

PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. - Xinyi Yu; Jiashun Xiao; Mingxuan Cai; Yuling Jiao; Xiang Wan; Jin Liu 011; Can Yang 002 (Bioinform., 2023)

Deep estimation for Q⁎ with minimax Bellman error minimization. - Lican Kang; Xu Liao; Jin Liu 011; Yuan Luo (Inf. Sci., 2023)

Deep Dimension Reduction for Supervised Representation Learning. - Jian Huang 003; Yuling Jiao; Xu Liao; Jin Liu 011; Zhou Yu (IEEE Trans. Inf. Theory, 2024)

Schrödinger-Föllmer Sampler. - Jian Huang 003; Yuling Jiao; Lican Kang; Xu Liao; Jin Liu 011; Yanyan Liu (IEEE Trans. Inf. Theory, 2025)

Model Free Prediction With Uncertainty Assessment. - Yuling Jiao; Lican Kang; Jin Liu 011; Heng Peng; Heng Zuo (IEEE Trans. Inf. Theory, 2025)