| Adaptive hypergraph auto-encoder for relational data clustering Y Hu, X Li, Y Wang, Y Wu, Y Zhao, C Yan, J Yin, Y Gao IEEE Transactions on Knowledge and Data Engineering 35 (3), 2231-2242, 2021 | 32 | 2021 |
| A deep graph structured clustering network X Li, Y Hu, Y Sun, J Hu, J Zhang, M Qu IEEE Access 8, 161727-161738, 2020 | 26 | 2020 |
| Internal consistency and self-feedback in large language models: A survey X Liang, S Song, Z Zheng, H Wang, Q Yu, X Li, RH Li, Y Wang, Z Wang, ... arXiv preprint arXiv:2407.14507, 2024 | 24 | 2024 |
| Towards Effective and General Graph Unlearning via Mutual Evolution X Li, Y Zhao, Z Wu, W Zhang, RH Li, G Wang AAAI 2024, 2024 | 15 | 2024 |
| FedGTA: Topology-aware Averaging for Federated Graph Learning X Li, Z Wu, W Zhang, Y Zhu, RH Li, G Wang VLDB 2024, 2024 | 12 | 2024 |
| Handling information loss of graph convolutional networks in collaborative filtering X Xiong, XK Li, YP Hu, YX Wu, J Yin Information systems 109, 102051, 2022 | 12 | 2022 |
| Rethinking Node-wise Propagation for Large-scale Graph Learning X Li, J Ma, Z Wu, D Su, W Zhang, RH Li, G Wang WWW 2024, 2024 | 8 | 2024 |
| FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning Y Zhu, X Li, Z Wu, D Wu, M Hu, RH Li arXiv preprint arXiv:2404.14061, 2024 | 7 | 2024 |
| Breaking the entanglement of homophily and heterophily in semi-supervised node classification H Sun, X Li, Z Wu, D Su, RH Li, G Wang 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2379-2392, 2024 | 6 | 2024 |
| Daohan Su, Wentao Zhang, Rong-Hua Li, and Guoren Wang. 2024. LightDiC: A Simple Yet Effective Approach for Large-Scale Digraph Representation Learning X Li, M Liao, Z Wu Proceedings of the VLDB Endowment, 2024 | 6 | 2024 |
| Effective hybrid graph and hypergraph convolution network for collaborative filtering X Li, R Guo, J Chen, Y Hu, M Qu, B Jiang Neural computing and applications 35 (3), 2633-2646, 2023 | 6 | 2023 |
| AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity X Li, Z Wu, W Zhang, H Sun, RH Li, G Wang ICDE 2024, 2024 | 5 | 2024 |
| A simple graph convolutional network with abundant interaction for collaborative filtering R Guo, X Li, Y Hu, Y Wu, X Xiong, M Qu IEEE Access 9, 77407-77415, 2021 | 5 | 2021 |
| Acceleration algorithms in gnns: A survey L Ma, Z Sheng, X Li, X Gao, Z Hao, L Yang, W Zhang, B Cui arXiv preprint arXiv:2405.04114, 2024 | 4 | 2024 |
| Daohan Su, Rong-Hua Li, and Guoren Wang. 2024. Breaking the Entanglement of Homophily and Heterophily in Semisupervised Node Classification H Sun, X Li, Z Wu International Conference on Data Engineering, ICDE, 2023 | 3 | 2023 |
| A new paradigm for federated structure non-iid subgraph learning X Li, W Zhang, RH Li, Y Zhao, Y Zhu, G Wang | 3 | 2023 |
| Siamese network based multiscale self-supervised heterogeneous graph representation learning Z Chen, L Luo, X Li, B Jiang, Q Guo, C Wang IEEE Access 10, 98490-98500, 2022 | 3 | 2022 |
| Openfgl: A comprehensive benchmarks for federated graph learning X Li, Y Zhu, B Pang, G Yan, Y Yan, Z Li, Z Wu, W Zhang, RH Li, G Wang arXiv preprint arXiv:2408.16288, 2024 | 2 | 2024 |
| A Scalable Deep Network for Graph Clustering via Personalized PageRank Y Zhao, X Li, Y Zhu, J Li, S Wang, B Jiang Applied Sciences 12 (11), 5502, 2022 | 2 | 2022 |
| DiRW: Path-Aware Digraph Learning for Heterophily D Su, X Li, Z Li, Y Liao, RH Li, G Wang arXiv preprint arXiv:2410.10320, 2024 | 1 | 2024 |
