| Dropedge: Towards deep graph convolutional networks on node classification Y Rong, W Huang, T Xu, J Huang International Conference on Learning Representations, 2019 | 1611 | 2019 |
| Self-Supervised Graph Transformer on Large-Scale Molecular Data Y Rong, Y Bian, T Xu, W Xie, Y Wei, W Huang, J Huang Advances in Neural Information Processing Systems 33, 2020 | 820 | 2020 |
| Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks T Bian, X Xiao, T Xu, P Zhao, W Huang, Y Rong, J Huang Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 549-556, 2020 | 657 | 2020 |
| Graph Representation Learning via Graphical Mutual Information Maximization Z Peng, W Huang, M Luo, Q Zheng, Y Rong, T Xu, J Huang Proceedings of The Web Conference 2020, 259-270, 2020 | 614 | 2020 |
| Graph Convolutional Networks for Temporal Action Localization R Zeng, W Huang, M Tan, Y Rong, P Zhao, J Huang, C Gan Proceedings of the IEEE International Conference on Computer Vision, 7094-7103, 2019 | 608 | 2019 |
| Adaptive sampling towards fast graph representation learning W Huang, T Zhang, Y Rong, J Huang Advances in neural information processing systems 31, 4558-4567, 2018 | 603 | 2018 |
| Progressive Feature Alignment for Unsupervised Domain Adaptation C Chen, W Xie, W Huang, Y Rong, X Ding, Y Huang, T Xu, J Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 500 | 2019 |
| Deep Multimodal Fusion by Channel Exchanging Y Wang, W Huang, F Sun, T Xu, Y Rong, J Huang Advances in Neural Information Processing Systems 33, 2020 | 270 | 2020 |
| FedGraphNN: A Federated Learning Benchmark System for Graph Neural Networks C He, K Balasubramanian, E Ceyani, C Yang, H Xie, L Sun, L He, L Yang, ... ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML), 2021 | 226* | 2021 |
| Graph Information Bottleneck for Subgraph Recognition J Yu, T Xu, Y Rong, Y Bian, J Huang, R He International Conference on Learning Representations (ICLR 2021), 2021 | 174 | 2021 |
| Transformer for Graphs: An Overview from Architecture Perspective E Min, R Chen, Y Bian, T Xu, K Zhao, W Huang, P Zhao, J Huang, ... arXiv preprint arXiv:2202.08455, 2022 | 167 | 2022 |
| A restricted black-box adversarial framework towards attacking graph embedding models H Chang, Y Rong, T Xu, W Huang, H Zhang, P Cui, W Zhu, J Huang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3389-3396, 2020 | 163 | 2020 |
| Semi-Supervised Graph Classification: A Hierarchical Graph Perspective J Li, Y Rong, H Cheng, H Meng, W Huang, J Huang The World Wide Web Conference, 972-982, 2019 | 163 | 2019 |
| Local augmentation for graph neural networks S Liu, R Ying, H Dong, L Li, T Xu, Y Rong, P Zhao, J Huang, D Wu International Conference on Machine Learning, 14054-14072, 2022 | 123 | 2022 |
| Cross-Dependent Graph Neural Networks for Molecular Property Prediction H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang Bioinformatics, 2022 | 123* | 2022 |
| Tackling Over-Smoothing for General Graph Convolutional Networks W Huang, Y Rong, T Xu, F Sun, J Huang arXiv preprint arXiv:2008.09864, 2020 | 114 | 2020 |
| Drugood: Out-of-distribution dataset curator and benchmark for ai-aided drug discovery–a focus on affinity prediction problems with noise annotations Y Ji, L Zhang, J Wu, B Wu, L Li, LK Huang, T Xu, Y Rong, J Ren, D Xue, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8023-8031, 2023 | 99* | 2023 |
| Adversarial Attack on Community Detection by Hiding Individuals J Li, H Zhang, Z Han, Y Rong, H Cheng, J Huang Proceedings of The Web Conference 2020, 917-927, 2020 | 96 | 2020 |
| Geometrically Equivariant Graph Neural Networks: A Survey J Han, Y Rong, T Xu, W Huang arXiv preprint arXiv:2202.07230, 2022 | 81 | 2022 |
| Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media E Min, Y Rong, Y Bian, T Xu, P Zhao, J Huang, S Ananiadou Proceedings of the ACM Web Conference 2022, 1148-1158, 2022 | 79 | 2022 |
Junzhou HuangJenkins Garrett Professor, Computer Science and Engineering, the University of Texas at Arlington在 uta.edu 的电子邮件经过验证
