| Graph contrastive learning with adaptive augmentation Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang Proceedings of the Web Conference 2021, 2069-2080, 2021 | 407 | 2021 |
| Deep graph contrastive representation learning Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang arXiv preprint arXiv:2006.04131, 2020 | 355 | 2020 |
| An Empirical Study of Graph Contrastive Learning Y Zhu, Y Xu, Q Liu, S Wu Proceedings of the Neural Information Processing Systems Track on Datasets …, 2021 | 64 | 2021 |
| CAGNN: Cluster-aware graph neural networks for unsupervised graph representation learning Y Zhu, Y Xu, F Yu, S Wu, L Wang arXiv preprint arXiv:2009.01674, 2020 | 21 | 2020 |
| A survey on deep graph generation: Methods and applications Y Zhu, Y Du, Y Wang, Y Xu, J Zhang, Q Liu, S Wu arXiv preprint arXiv:2203.06714, 2022 | 10 | 2022 |
| Structure-enhanced heterogeneous graph contrastive learning Y Zhu, Y Xu, H Cui, C Yang, Q Liu, S Wu Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 9 | 2022 |
| Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction Y Xu, Y Zhu, F Yu, Q Liu, S Wu, L Wang Proceedings of the 30th ACM International Conference on Information and …, 2021 | 9 | 2021 |
| Structure-aware hard negative mining for heterogeneous graph contrastive learning Y Zhu, Y Xu, H Cui, C Yang, Q Liu, S Wu arXiv preprint arXiv:2108.13886, 2021 | 5 | 2021 |
| A case for DOT: theoretical foundations for objects with pattern matching and GADT-style reasoning A Boruch-Gruszecki, R Waśko, Y Xu, L Parreaux Proceedings of the ACM on Programming Languages 6 (OOPSLA2), 1526-1555, 2022 | 2 | 2022 |
| Implementing path-dependent GADT reasoning for Scala 3 Y Xu, A Boruch-Gruszecki, L Parreaux Proceedings of the 12th ACM SIGPLAN International Symposium on Scala, 22-32, 2021 | 1 | 2021 |
| A Survey on Pretrained Language Models for Neural Code Intelligence Y Xu, Y Zhu arXiv preprint arXiv:2212.10079, 2022 | | 2022 |
Yanqiao ZHUUniversity of California, Los Angeles在 cs.ucla.edu 的电子邮件经过验证
