| A comprehensive survey on graph neural networks Z Wu, S Pan, F Chen, G Long, C Zhang, PS Yu IEEE Transactions on Neural Networks and Learning Systems 32 (1), 4-24, 2020 | 14761 | 2020 |
| A survey on knowledge graphs: Representation, acquisition and applications S Ji, S Pan, E Cambria, P Marttinen, PS Yu IEEE Transactions on Neural Networks and Learning Systems 33 (2), 494 - 514, 2021 | 3633 | 2021 |
| Graph WaveNet for Deep Spatial-Temporal Graph Modeling Z Wu, S Pan, G Long, J Jiang, C Zhang International Joint Conference on Artificial Intelligence, IJCAI-19, 2019 | 3504 | 2019 |
| Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks Z Wu, S Pan, G Long, J Jiang, X Chang, C Zhang ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD-20, 2020 | 2468 | 2020 |
| Unifying Large Language Models and Knowledge Graphs: A Roadmap S Pan, L Luo, Y Wang, C Chen, J Wang, X Wu IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024 | 1661 | 2024 |
| Adversarially Regularized Graph Autoencoder for Graph Embedding S Pan, R Hu, G Long, J Jiang, L Yao, C Zhang International Joint Conference on Artificial Intelligence, IJCAI-18, 2609-2615, 2018 | 1282 | 2018 |
| TIME-LLM: TIME SERIES FORECASTING BY REPRO-GRAMMING LARGE LANGUAGE MODELS M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ... International Conference on Learning Representations (ICLR), 2024 | 1243 | 2024 |
| DiSAN: Directional self-attention network for rnn/cnn-free language understanding T Shen, T Zhou, G Long, J Jiang, S Pan, C Zhang AAAI Conference on Artificial Intelligence, AAAI-18, 2018 | 970 | 2018 |
| Graph self-supervised learning: A survey Y Liu, M Jin, S Pan, C Zhou, Y Zheng, F Xia, PS Yu IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 | 847 | 2022 |
| Attributed Graph Clustering: A Deep Attentional Embedding Approach C Wang, S Pan, R Hu, G Long, J Jiang, C Zhang International Joint Conference on Artificial Intelligence, IJCAI-19, 2019 | 746 | 2019 |
| Graph Learning: A Survey F Xia, K Sun, S Yu, A Aziz, L Wan, S Pan, H Liu IEEE Transactions on Artificial Intelligence (TAI), 2021 | 627 | 2021 |
| MGAE: Marginalized graph autoencoder for graph clustering C Wang, S Pan, G Long, X Zhu, J Jiang CIKM 2017 - Proceedings of the 2017 ACM on Conference on Information and …, 2017 | 614 | 2017 |
| Tri-Party Deep Network Representation S Pan, J Wu, X Zhu, C Zhang, Y Wang International Joint Conference on Artificial Intelligence, IJCAI-16, 1895-1901, 2016 | 563 | 2016 |
| A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detection M Jin, HY Koh, Q Wen, D Zambon, C Alippi, GI Webb, I King, S Pan IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024 | 539 | 2024 |
| Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning Y Liu, Z Li, S Pan, C Gong, C Zhou, G Karypis IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 | 530 | 2021 |
| Deep learning for time series anomaly detection: A survey ZZ Darban, GI Webb, S Pan, CC Aggarwal, M Salehi ACM Computing Surveys (CSUR), 2024 | 515* | 2024 |
| A survey of community detection approaches: From statistical modeling to deep learning D Jin, Z Yu, P Jiao, S Pan, PS Yu, W Zhang IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021 | 514 | 2021 |
| Reasoning on graphs: Faithful and interpretable large language model reasoning L Luo, YF Li, G Haffari, S Pan International Conference on Learning Representations (ICLR), 2024 | 470 | 2024 |
| Learning graph embedding with adversarial training methods S Pan, R Hu, S Fung, G Long, J Jiang, C Zhang IEEE Transactions on Cybernetics (TCYB), 2020 | 419 | 2020 |
| Foundation models for time series analysis: A tutorial and survey Y Liang, H Wen, Y Nie, Y Jiang, M Jin, D Song, S Pan, Q Wen ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 | 399 | 2024 |
Chengqi ZhangChair Professor of Artificial IntelligenceVerified email at polyu.edu.hk
