| Graph attention multi-layer perceptron W Zhang, Z Yin, Z Sheng, Y Li, W Ouyang, X Li, Y Tao, Z Yang, B Cui Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 93 | 2022 |
| Node dependent local smoothing for scalable graph learning W Zhang, M Yang, Z Sheng, Y Li, W Ouyang, Y Tao, Z Yang, B Cui Advances in Neural Information Processing Systems 34, 20321-20332, 2021 | 47 | 2021 |
| Model degradation hinders deep graph neural networks W Zhang, Z Sheng, Z Yin, Y Jiang, Y Xia, J Gao, Z Yang, B Cui Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 29 | 2022 |
| Evaluating deep graph neural networks W Zhang, Z Sheng, Y Jiang, Y Xia, J Gao, Z Yang, B Cui arXiv preprint arXiv:2108.00955, 2021 | 27 | 2021 |
| ROD: reception-aware online distillation for sparse graphs W Zhang, Y Jiang, Y Li, Z Sheng, Y Shen, X Miao, L Wang, Z Yang, B Cui Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 23 | 2021 |
| NAFS: a simple yet tough-to-beat baseline for graph representation learning W Zhang, Z Sheng, M Yang, Y Li, Y Shen, Z Yang, B Cui International Conference on Machine Learning, 26467-26483, 2022 | 14 | 2022 |
| Graph attention MLP with reliable label utilization W Zhang, Z Yin, Z Sheng, W Ouyang, X Li, Y Tao, Z Yang, B Cui arXiv preprint arXiv:2108.10097, 2021 | 2 | 2021 |
| HGAMLP: A Scalable Training Framework for Heterogeneous Graph Learning Y Liang, W Zhang, Z Sheng, L Yang, J Jiang, Y Tong, CUI Bin | | |
Bin CUIProfessor of Computer Science, Peking UniversityVerified email at pku.edu.cn
