Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding X Fu, J Zhang, Z Meng, I King Proceedings of the web conference 2020, 2331-2341, 2020 | 732 | 2020 |
Modeling scale-free graphs with hyperbolic geometry for knowledge-aware recommendation Y Chen, M Yang, Y Zhang, M Zhao, Z Meng, J Hao, I King Proceedings of the fifteenth ACM international conference on web search and …, 2022 | 68 | 2022 |
Graph-adaptive rectified linear unit for graph neural networks Y Zhang, H Zhu, Z Meng, P Koniusz, I King Proceedings of the ACM Web Conference 2022, 1331-1339, 2022 | 29 | 2022 |
Featurenorm: L2 feature normalization for dynamic graph embedding M Yang, Z Meng, I King 2020 IEEE International Conference on Data Mining (ICDM), 731-740, 2020 | 25 | 2020 |
Semi-supervised multi-label learning for graph-structured data Z Song, Z Meng, Y Zhang, I King Proceedings of the 30th ACM International Conference on Information …, 2021 | 24 | 2021 |
Meta-learning with motif-based task augmentation for few-shot molecular property prediction Z Meng, Y Li, P Zhao, Y Yu, I King Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 9 | 2023 |
A unified view of deep learning for reaction and retrosynthesis prediction: Current status and future challenges Z Meng, P Zhao, Y Yu, I King arXiv preprint arXiv:2306.15890, 2023 | 4 | 2023 |
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping H Wang, G Ma, Z Meng, Z Qin, L Shen, Z Zhang, B Wu, L Liu, Y Bian, T Xu, ... arXiv preprint arXiv:2402.07610, 2024 | 3 | 2024 |
Doubly stochastic graph-based non-autoregressive reaction prediction Z Meng, P Zhao, Y Yu, I King arXiv preprint arXiv:2306.06119, 2023 | 3 | 2023 |
A Diffusion-Based Pre-training Framework for Crystal Property Prediction Z Song, Z Meng, I King Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8993-9001, 2024 | | 2024 |
Understanding Graph Neural Networks via Trajectory Analysis Z Meng, J Dong, Z Huang, I King | | |