Attributed Network Embedding for Incomplete Structure Information. - Chengbin Hou; Shan He 001; Ke Tang 001 (CoRR, 2018)

Learning Topological Representation for Networks via Hierarchical Sampling. - Guoji Fu; Chengbin Hou; Xin Yao 001 (IJCNN, 2019)

DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding. - Chengbin Hou; Han Zhang; Ke Tang 001; Shan He 001 (CoRR, 2019)

RoSANE: Robust and scalable attributed network embedding for sparse networks. - Chengbin Hou; Shan He 001; Ke Tang 001 (Neurocomputing, 2020)

A Network Embedding Based Approach to Drug-Target Interaction Prediction Using Additional Implicit Networks. - Han Zhang; Chengbin Hou; David W. McDonald; Shan He 001 (ICANN (1), 2021)

Towards Robust Dynamic Network Embedding. - Chengbin Hou; Ke Tang 001 (IJCAI, 2021)

Robust Dynamic Network Embedding via Ensembles. - Chengbin Hou; Guoji Fu; Peng Yang 008; Shan He 001; Ke Tang 001 (CoRR, 2021)

GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract). - Chengbin Hou; Han Zhang; Shan He 001; Ke Tang 001 (ICDE, 2022)

Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. - Bingzhe Wu; Jintang Li; Chengbin Hou; Guoji Fu; Yatao Bian; Liang Chen 001; Junzhou Huang (CoRR, 2022)

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. - Bingzhe Wu; Jintang Li; Junchi Yu; Yatao Bian; Hengtong Zhang; Chaochao Chen 001; Chengbin Hou; Guoji Fu; Liang Chen 001; Tingyang Xu; Yu Rong 001; Xiaolin Zheng; et al. (CoRR, 2022)

GloDyNE: Global Topology Preserving Dynamic Network Embedding. - Chengbin Hou; Han Zhang; Shan He 001; Ke Tang 001 (IEEE Trans. Knowl. Data Eng., 2022)

Network embedding and its applications. - Chengbin Hou (2022)

Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews. - Chengbin Hou; Xinyu Lin; Hanhui Huang; Sheng Xu; Junxuan Fan; Yukun Shi; Hairong Lv (CoRR, 2023)

Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models. - Tianyu Zhang; Yuxiang Ren; Chengbin Hou; Hairong Lv; Xuegong Zhang (BIBM, 2024)

Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning. - Hongze Zhu; Guoyang Xie; Chengbin Hou; Tao Dai 001; Can Gao; Jinbao Wang; Linlin Shen (ACM Multimedia, 2024)

Parse Trees Guided LLM Prompt Compression. - Wenhao Mao; Chengbin Hou; Tianyu Zhang; Xinyu Lin; Ke Tang 001; Hairong Lv (CoRR, 2024)

Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs. - Xinyu Lin; Tianyu Zhang; Chengbin Hou; Jinbao Wang; Jianye Xue; Hairong Lv (CoRR, 2024)

Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection. - Hanzhe Liang; Guoyang Xie; Chengbin Hou; Bingshu Wang; Can Gao; Jinbao Wang (AAAI, 2025)

FedAGHN: Personalized Federated Learning with Attentive Graph HyperNetworks. - Jiarui Song; Yunheng Shen; Chengbin Hou; Pengyu Wang; Jinbao Wang; Ke Tang 001; Hairong Lv (CoRR, 2025)

Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs. - Tianyu Zhang; Chengbin Hou; Rui Jiang 001; Xuegong Zhang; Chenghu Zhou; Ke Tang 001; Hairong Lv (IEEE Trans. Neural Networks Learn. Syst., 2025)