A comprehensive survey on graph neural networks Z Wu, S Pan, F Chen, G Long, C Zhang, SY Philip IEEE transactions on neural networks and learning systems 32 (1), 4-24, 2020 | 9197 | 2020 |
Graph wavenet for deep spatial-temporal graph modeling Z Wu, S Pan, G Long, J Jiang, C Zhang Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 1870 | 2019 |
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks Z Wu, S Pan, G Long, J Jiang, X Chang, C Zhang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 1217 | 2020 |
Personalized federated learning with graph F Chen, G Long, Z Wu, T Zhou, J Jiang (IJCAI) International Joint Conference on Artificial Intelligence 2022, 2575 …, 2022 | 63 | 2022 |
Spatio-temporal joint graph convolutional networks for traffic forecasting C Zheng, X Fan, S Pan, H Jin, Z Peng, Z Wu, C Wang, SY Philip IEEE Transactions on Knowledge and Data Engineering 36 (1), 372-385, 2023 | 34 | 2023 |
Traversenet: Unifying space and time in message passing for traffic forecasting Z Wu, D Zheng, S Pan, Q Gan, G Long, G Karypis IEEE Transactions on Neural Networks and Learning Systems 35 (2), 2003-2013, 2022 | 28 | 2022 |
Heterogeneous graph attention network for small and medium-sized enterprises bankruptcy prediction Y Zheng, VCS Lee, Z Wu, S Pan Pacific-Asia Conference on Knowledge Discovery and Data Mining, 140-151, 2021 | 27 | 2021 |
Beyond low-pass filtering: Graph convolutional networks with automatic filtering Z Wu, S Pan, G Long, J Jiang, C Zhang IEEE Transactions on Knowledge and Data Engineering 35 (7), 6687-6697, 2022 | 18 | 2022 |
Collaborative filtering fusing label features based on SDAE H Huo, X Liu, D Zheng, Z Wu, S Yu, L Liu Advances in Data Mining. Applications and Theoretical Aspects: 17th …, 2017 | 7 | 2017 |
Contig: Continuous representation learning on temporal interaction graphs Z Wang, P Yang, X Fan, X Yan, Z Wu, S Pan, L Chen, Y Zang, C Wang, ... Neural Networks 172, 106151, 2024 | 4 | 2024 |