Publications
Yilong Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang. “HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training.” CIKM 2025.
Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang. “A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability.” Machine Intelligence Research (MIR).
Tianxiang Zhao, Xiang Zhang, Suhang Wang. “Imbalanced Node Classification with Synthetic Over-sampling.” TKDE
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. “Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling.” KDD 2024
Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Xiao Liu, Wenchao Yu, Haifeng Chen, Xiang Zhang. “Towards Inductive and Efficient Explanations for Graph Neural Networks.” TPAMI
Tianxiang Zhao, Xiang Zhang, Suhang Wang. “Disambiguated Node Classification with Graph Neural Networks.” WebConf (WWW) 2024. [paper][code]
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen. “Interpretable Imitation Learning with Dynamic Causal Relations.” WSDM 2024 Oral. [paper]
Fali Wang, Tianxiang Zhao, Suhang Wang. “Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels”. WSDM 2024.
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. “Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment.” TIST [paper]
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen. “Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations.” KDD 2023. [paper] [codes]
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. “TopoImb: Toward Topology-level Imbalance in Learning from Graphs.” LOG 2023. [paper]
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. “Towards Faithful and Consistent Explanations for Graph Neural Networks.” WSDM 2023. [paper]
Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao. “Explanation guided contrastive learning for sequential recommendation”. Accepted by CIKM 2022.
Tianxiang Zhao, Xiang Zhang, Suhang Wang. “Exploring Edge Disentanglement for Node Classification.” WebConf (WWW) 2022. [paper][codes]
Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai. “Times series forecasting for urban building energy consumption based on graph convolutional network”. Accepted by Applied Energy 2022.
Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang. “You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features.” WSDM 2022.[codes]
Tianxiang Zhao, Xiang Zhang, Suhang Wang. “GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks.” WSDM 2021.[codes]
Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang. “Semi-Supervised Graph-to-Graph Translation.” CIKM 2020.
AS Adishesha, Tianxiang Zhao. “Emotion Embedded Pose Generation”. ECCV 2020 workshop.
Tianxiang Zhao, Lemao Liu, Huayang Li, Guoping Huang, Enhong Chen, Guiquan Liu, Shuming Shi. “Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation.” AAAI 2020.
Tianxiang Zhao, Guiquan Liu, Le Wu, Chao Ma, Enhong Chen. “Energy Based Model for Zero Shot Learning.” regular paper. ICDM 2018.
Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, Enhong Chen. “Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach.” short paper. ICDM 2018.