Publications

Preprints

1. Shape-aware Graph Spectral Learning
   Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang
   Submitted to ICLR 2024 [Paper]

2. Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang

Conference Paper

1. HP-GMN:Graph Memory Networks for Heterophilous Graphs
   Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang
   The IEEE International Conference on Data Mining (ICDM 2022) [Paper] [Code]

2. Revisiting Time Series Outlier Detection: Definitions and Benchmarks
   Kwei-Herng Lai, Daochen Zha, Junjie Xu, Yue Zhao, Guanchu Wang, Xia Hu
   Neural Information Processing Systems, Datasets and Benchmarks Track (NeurIPS 2021) [Paper] [Code]

3. TODS: An Automated Time Series Outlier Detection System
   Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Mingyang Wan, Diego Martinez, Xia Hu
   AAAI Conference on Artificial Intelligence, demo track (AAAI 2021) [Paper] [Code]

Journal Paper

1. A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
   Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
   Machine Intelligence Research [Paper]