Heterogeneous Similarity Graph Neural Network on Electronic Health Records. - Zheng Liu 017; Xiaohan Li 001; Hao Peng 001; Lifang He 001; Philip S. Yu (IEEE BigData, 2020)

Dynamic Graph Collaborative Filtering. - Xiaohan Li 001; Mengqi Zhang; Shu Wu; Zheng Liu 017; Liang Wang 001; Philip S. Yu (ICDM, 2020)

Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. - Xiaohan Li 001; Zhiwei Liu 001; Stephen D. Guo; Zheng Liu 017; Hao Peng 001; Philip S. Yu; Kannan Achan (IEEE BigData, 2021)

Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. - Zheng Liu 017; Xiaohan Li 001; Zeyu You; Tao Yang 012; Wei Fan 001; Philip S. Yu (SIGIR, 2021)

Mitigating health disparities in EHR via deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (BCB, 2022)

Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. - Xiaohan Li 001; Yuqing Liu 003; Zheng Liu 017; Philip S. Yu (IEEE Big Data, 2022)

Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. - Xiaohan Li 001; Zheng Liu 017; Luyi Ma; Kaushiki Nag; Stephen D. Guo; Philip S. Yu; Kannan Achan (IEEE Big Data, 2022)

A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (ICDM, 2023)

Mitigating Health Disparity on Biased Electronic Health Records via Deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (CoRR, 2023)