An Efficient Subgraph-Inferring Framework for Large-Scale Heterogeneous Graphs. - Wei Zhou; Hong Huang 001; Ruize Shi; Kehan Yin; Hai Jin 001 (AAAI, 2024)

CausalNET: Unveiling Causal Structures on Event Sequences by Topology-Informed Causal Attention. - Hua Zhu; Hong Huang 001; Kehan Yin; Zejun Fan; Hai Jin 001; Bang Liu (IJCAI, 2024)

Orthogonality Matters: Invariant Time Series Representation for Out-of-distribution Classification. - Ruize Shi; Hong Huang 001; Kehan Yin; Wei Zhou; Hai Jin 001 (KDD, 2024)

OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework. - Wei Zhou; Hong Huang 001; Guowen Zhang; Ruize Shi; Kehan Yin; Yuanyuan Lin; Bang Liu (CoRR, 2024)

From General to Specific: Tailoring Large Language Models for Personalized Healthcare. - Ruize Shi; Hong Huang 001; Wei Zhou; Kehan Yin; Kai Zhao; Yun Zhao (CoRR, 2024)

Efficient Learning for Billion-Scale Heterogeneous Information Networks. - Ruize Shi; Hong Huang 001; Xue Lin 005; Kehan Yin; Wei Zhou; Hai Jin 001 (IEEE Trans. Big Data, 2025)