Publications
Published (* denotes Equal Contribution)
24. Learning Graph Quantized Tokenizers for Transformers
🔻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
🔻[To Appear]
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, Top 2.08% Over 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)
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)
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
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
🔻[Paper] [Slides] [Video] [Data & Code]
8. Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future
🔻Dongqi Fu, Jingrui He
🔻Frontiers in Big Data, December 2022
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
🔻[Paper] [Slides] [Demo] [Code]
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
🔻[Paper] [Slides] [Video] [Code]
3. SDG: A Simplified and Dynamic Graph Neural Network
🔻Dongqi Fu, Jingrui He
🔻SIGIR 2021
🔻[Paper] [Slides] [Video] [Code]
2. A View-Adversarial Framework for Multi-View Network Embedding
🔻Dongqi Fu*, Zhe Xu*, Bo Li, Hanghang Tong, Jingrui He
🔻CIKM 2020
🔻[Paper] [Slides] [Video] [Code]
1. Local Motif Clustering on Time-Evolving Graphs
🔻Dongqi Fu, Dawei Zhou, Jingrui He
🔻KDD 2020