| Searching lottery tickets in graph neural networks: A dual perspective K Wang, Y Liang, P Wang, X Wang, P Gu, J Fang, Y Wang The Eleventh International Conference on Learning Representations, 2022 | 23 | 2022 |
| Cooperative explanations of graph neural networks J Fang, X Wang, A Zhang, Z Liu, X He, TS Chua Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 21 | 2023 |
| Evaluating post-hoc explanations for graph neural networks via robustness analysis J Fang, W Liu, Y Gao, Z Liu, A Zhang, X Wang, X He Advances in Neural Information Processing Systems 36, 2024 | 16 | 2024 |
| Exgc: Bridging efficiency and explainability in graph condensation J Fang, X Li, Y Sui, Y Gao, G Zhang, K Wang, X Wang, X He Proceedings of the ACM on Web Conference 2024, 721-732, 2024 | 9 | 2024 |
| Modeling spatio-temporal dynamical systems with neural discrete learning and levels-of-experts K Wang, H Wu, G Zhang, J Fang, Y Liang, Y Wu, R Zimmermann, Y Wang IEEE Transactions on Knowledge and Data Engineering, 2024 | 8 | 2024 |
| Moltc: Towards molecular relational modeling in language models J Fang, S Zhang, C Wu, Z Yang, Z Liu, S Li, K Wang, W Du, X Wang arXiv preprint arXiv:2402.03781, 2024 | 8 | 2024 |
| On regularization for explaining graph neural networks: An information theory perspective J Fang, W Liu, A Zhang, X Wang, X He, K Wang, TS Chua | 8 | 2023 |
| Two heads are better than one: Boosting graph sparse training via semantic and topological awareness G Zhang, Y Yue, K Wang, J Fang, Y Sui, K Wang, Y Liang, D Cheng, ... arXiv preprint arXiv:2402.01242, 2024 | 6 | 2024 |
| The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs K Wang, G Zhang, X Zhang, J Fang, X Wu, G Li, S Pan, W Huang, Y Liang arXiv preprint arXiv:2406.12539, 2024 | | 2024 |
| Fortune favors the invariant: Enhancing GNNs’ generalizability with Invariant Graph Learning G Zhang, Y Chen, S Wang, K Wang, J Fang Knowledge-Based Systems 292, 111620, 2024 | | 2024 |
| Invariant Graph Learning for Causal Effect Estimation Y Sui, C Tang, Z Chu, J Fang, Y Gao, Q Cui, L Li, J Zhou, X Wang Proceedings of the ACM on Web Conference 2024, 2552-2562, 2024 | | 2024 |
| Graph Anomaly Detection with Bi-level Optimization Y Gao, J Fang, Y Sui, Y Li, X Wang, H Feng, Y Zhang Proceedings of the ACM on Web Conference 2024, 4383-4394, 2024 | | 2024 |
| Invariant Graph Learning for Treatment Effect Estimation from Networked Observational Data Y Sui, C Tang, Z Chu, J Fang, Y Gao, Q Cui, L Li, JUN ZHOU, X Wang The Web Conference 2024, 0 | | |
Xiang WangUniversity of Science and Technology of China在 ustc.edu.cn 的电子邮件经过验证
