Statistical Estimation of Diffusion Network Topologies. - Keqi Han; Yuan Tian; Yunjia Zhang; Ling Han; Hao Huang 001; Yunjun Gao (ICDE, 2020)

Diffusion Network Inference from Partial Observations. - Ting Gan; Keqi Han; Hao Huang 001; Shi Ying; Yunjun Gao; Zongpeng Li (AAAI, 2021)

Reconstructing Diffusion Networks from Incomplete Data. - Hao Huang 001; Keqi Han; Beicheng Xu; Ting Gan (IJCAI, 2022)

Multi-aspect Diffusion Network Inference. - Hao Huang 001; Keqi Han; Beicheng Xu; Ting Gan (WWW, 2023)

Learning Diffusions under Uncertainty. - Hao Huang 001; Qian Yan 001; Keqi Han; Ting Gan; Jiawei Jiang 001; Quanqing Xu; Chuanhui Yang (AAAI, 2024)

Multi-task Learning for Brain Network Analysis in the ABCD Study. - Xuan Kan; Hejie Cui; Keqi Han; Ying Guo 003; Carl Yang 001 (BHI, 2024)

End-to-End Deep Learning for Structural Brain Imaging: A Unified Framework. - Yao Su 003; Keqi Han; Mingjie Zeng; Lichao Sun 001; Liang Zhan; Carl Yang 001; Lifang He 001; Xiangnan Kong (AAAI Spring Symposia, 2025)

Causal Brain Connectivity: Integrating Granger Directed Graphs in fMRI Analysis. - Tianyi Zhang; Keqi Han; Jiawei Nie; Chenyu You; Sanne J. H. van Rooij; Jennifer S. Stevens; Boadie Dunlop; Charles Gillespie; Carl Yang 001 (AIME (2), 2025)

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? - Keqi Han; Yao Su 003; Lifang He 001; Liang Zhan; Sergey M. Plis; Vince D. Calhoun; Carl Yang 001 (CoRR, 2025)