Dropedge: Towards deep graph convolutional networks on node classification Y Rong, W Huang, T Xu, J Huang International Conference on Learning Representations, 2019 | 1413 | 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 | 643 | 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 | 565 | 2020 |
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 | 552 | 2018 |
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 | 548 | 2019 |
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 | 531 | 2020 |
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 | 453 | 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 | 222 | 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 | 182* | 2021 |
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 | 147 | 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 | 145 | 2019 |
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 | 142 | 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 | 109 | 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 | 98 | 2020 |
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 | 97 | 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 | 97* | 2022 |
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 | 87 | 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 | 80* | 2023 |
Geometrically Equivariant Graph Neural Networks: A Survey J Han, Y Rong, T Xu, W Huang arXiv preprint arXiv:2202.07230, 2022 | 62 | 2022 |
Molecular graph enhanced transformer for retrosynthesis prediction K Mao, X Xiao, T Xu, Y Rong, J Huang, P Zhao Neurocomputing 457, 193-202, 2021 | 60 | 2021 |