| Data augmentation for deep graph learning: A survey K Ding, Z Xu, H Tong, H Liu ACM SIGKDD Explorations Newsletter 24 (2), 61-77, 2022 | 231 | 2022 |
| Graph sanitation with application to node classification Z Xu, B Du, H Tong Proceedings of the ACM Web Conference 2022, 1136-1147, 2022 | 36 | 2022 |
| A view-adversarial framework for multi-view network embedding D Fu, Z Xu, B Li, H Tong, J He Proceedings of the 29th ACM International Conference on Information …, 2020 | 32 | 2020 |
| Kernel ridge regression-based graph dataset distillation Z Xu, Y Chen, M Pan, H Chen, M Das, H Yang, H Tong Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 31 | 2023 |
| Node classification beyond homophily: Towards a general solution Z Xu, Y Chen, Q Zhou, Y Wu, M Pan, H Yang, H Tong Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 15 | 2023 |
| Relation Extraction Using Supervision from Topic Knowledge of Relation Labels. H Jiang, L Cui, Z Xu, D Yang, J Chen, C Li, J Liu, J Liang, C Wang, Y Xiao, ... IJCAI, 5024-5030, 2019 | 9 | 2019 |
| Calliope-net: Automatic generation of graph data facts via annotated node-link diagrams Q Chen, N Chen, W Shuai, G Wu, Z Xu, H Tong, N Cao IEEE Transactions on Visualization and Computer Graphics, 2023 | 7 | 2023 |
| Topological augmentation for class-imbalanced node classification Z Liu, Z Zeng, R Qiu, H Yoo, D Zhou, Z Xu, Y Zhu, K Weldemariam, J He, ... arXiv preprint arXiv:2308.14181, 2023 | 6 | 2023 |
| SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter H Xu, Y Yan, D Wang, Z Xu, Z Zeng, TF Abdelzaher, J Han, H Tong Forty-first International Conference on Machine Learning, 2024 | 5 | 2024 |
| Generalized Few-Shot Node Classification Z Xu, K Ding, YX Wang, H Liu, H Tong IEEE International Conference on Data Mining (ICDM), 2022 | 5 | 2022 |
| Graph Mixup on Approximate Gromov–Wasserstein Geodesics Z Zeng, R Qiu, Z Xu, Z Liu, Y Yan, T Wei, L Ying, J He, H Tong Forty-first International Conference on Machine Learning, 2024 | 4 | 2024 |
| Natural and Artificial Dynamics in GNNs: A Tutorial D Fu, Z Xu, H Tong, J He Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 4 | 2023 |
| Destine: Dense subgraph detection on multi-layered networks Z Xu, S Zhang, Y Xia, L Xiong, J Xu, H Tong Proceedings of the 30th ACM International Conference on Information …, 2021 | 3 | 2021 |
| Ranking on network of heterogeneous information networks Z Xu, S Zhang, Y Xia, L Xiong, H Tong 2020 IEEE International Conference on Big Data (Big Data), 848-857, 2020 | 3 | 2020 |
| Masked graph transformer for large-scale recommendation H Chen, Z Xu, CCM Yeh, V Lai, Y Zheng, M Xu, H Tong Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | 2 | 2024 |
| Class-Imbalanced Graph Learning without Class Rebalancing Z Liu, R Qiu, Z Zeng, H Yoo, D Zhou, Z Xu, Y Zhu, K Weldemariam, J He, ... Forty-first International Conference on Machine Learning, 2024 | 2 | 2024 |
| Discrete-state Continuous-time Diffusion for Graph Generation Z Xu, R Qiu, Y Chen, H Chen, X Fan, M Pan, Z Zeng, M Das, H Tong arXiv preprint arXiv:2405.11416, 2024 | 1 | 2024 |
| Generalized few-shot node classification: toward an uncertainty-based solution Z Xu, K Ding, YX Wang, H Liu, H Tong Knowledge and Information Systems 66 (2), 1205-1229, 2024 | 1 | 2024 |
| Learning optimal propagation for graph neural networks B Zhao, B Du, Z Xu, L Li, H Tong arXiv preprint arXiv:2205.02998, 2022 | 1 | 2022 |
| Dense subgraph detection on multi-layered networks Z Xu University of Illinois at Urbana-Champaign, 2021 | 1 | 2021 |
Hanghang TongUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
