Publications
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Preprint (* denotes Equal Contribution)
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs
🔻 Dongqi Fu*, Liri Fang*, Zihao Li*, Hanghang Tong, Vetle I Torvik, Jingrui He
🔻 [Paper]
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Published (* denotes Equal Contribution)
24. Learning Graph Quantized Tokenizers
🔻 Limei Wang*, Kaveh Hassani*, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long
🔻 ICLR 2025
🔻 [To Appear]
23. Temporal Heterogeneous Graph Generation with Privacy, Utility, and Efficiency
🔻 Xinyu He*, Dongqi Fu*, Hanghang Tong, Ross Maciejewski, Jingrui He
🔻 ICLR 2025 ( 🏆 Spotlight, 3.20% of 11,672 Submissions )
🔻 [To Appear] [Invited Talk at TGL on 04/17/2025]
22. Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
🔻 Katherine Tieu, Dongqi Fu, Jun Wu, Jingrui He
🔻 AISTATS 2025
🔻 [To Appear]
21. APEX²: Adaptive and Extreme Summarization for Personalized Knowledge Graphs
🔻 Zihao Li, Dongqi Fu, Mengting Ai, Jingrui He
🔻 KDD 2025
🔻 [To Appear]
20. Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
🔻 Katherine Tieu*, Dongqi Fu*, Yada Zhu, Hendrik Hamann, Jingrui He
🔻 NeurIPS 2024
19. PageRank Bandits for Link Prediction
🔻 Yikun Ban*, Jiaru Zou*, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He
🔻 NeurIPS 2024
18. BackTime: Backdoor Attacks on Multivariate Time Series Forecasting
🔻 Xiao Lin, Zhining Liu, Dongqi Fu, Ruizhong Qiu, Hanghang Tong
🔻 NeurIPS 2024 ( 🏆 Spotlight, 2.08% of 15,671 Submissions )
17. DrGNN: Deep Residual Graph Neural Network with Contrastive Learning
🔻 Lecheng Zheng*, Dongqi Fu*, Ross Maciejewski, Jingrui He
🔻 TMLR, October 2024
16. Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection
🔻 Dongqi Fu, Yada Zhu, Hanghang Tong, Kommy Weldemariam, Onkar Bhardwaj, Jingrui He
🔻 ICML 2024 (AI4Science Workshop)
🔻 [Paper]
15. VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
🔻 Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long
🔻 ICLR 2024
14. Investigating Natural and Artificial Dynamics in Graph Data Mining and Machine Learning
🔻 Dongqi Fu
🔻 CIKM 2023 (Doctoral Symposium)
🔻 [Paper]
13. Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
🔻 Dongqi Fu*, Wenxuan Bao*, Ross Maciejewski, Hanghang Tong, Jingrui He
🔻 SIGKDD Explorations, June 2023
🔻 [Paper]
12. Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs
🔻 Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He
🔻 WWW 2023
11. Everything Evolves in Personalized PageRank
🔻 Zihao Li*, Dongqi Fu*, Jingrui He
🔻 WWW 2023
10. Natural and Artificial Dynamics in GNNs: A Tutorial
🔻 Dongqi Fu, Zhe Xu, Hanghang Tong, Jingrui He
🔻 WSDM 2023 (Tutorial)
9. DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data
🔻 Dongqi Fu, Jingrui He
🔻 IEEE BigData 2022
8. Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future
🔻 Dongqi Fu, Jingrui He
🔻 Frontiers in Big Data, December 2022
🔻 [Paper]
7. MentorGNN: Deriving Curriculum for Pre-Training GNNs
🔻 Dawei Zhou*, Lecheng Zheng*, Dongqi Fu, Jiawei Han, Jingrui He
🔻 CIKM 2022
6. DISCO: Comprehensive and Explainable Disinformation Detection
🔻 Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He
🔻 CIKM 2022
5. Privacy-preserving Graph Analytics: Secure Generation and Federated Learning
🔻 Dongqi Fu, Jingrui He, Hanghang Tong, Ross Maciejewski
🔻 DHS CAOE Workshop on Privacy Enhancing Technologies for the Homeland Security Enterprise 2022
4. Meta-Learned Metrics over Multi-Evolution Temporal Graphs
🔻 Dongqi Fu*, Liri Fang*, Ross Maciejewski, Vetle I Torvik, Jingrui He
🔻 KDD 2022
3. SDG: A Simplified and Dynamic Graph Neural Network
🔻 Dongqi Fu, Jingrui He
🔻 SIGIR 2021
2. A View-Adversarial Framework for Multi-View Network Embedding
🔻 Dongqi Fu*, Zhe Xu*, Bo Li, Hanghang Tong, Jingrui He
🔻 CIKM 2020