| Graph WaveNet for Deep Spatial-Temporal Graph Modeling Z Wu, S Pan, G Long, J Jiang, C Zhang (IJCAI-2019) the Twenty-Eighth International Joint Conference on Artificial …, 2019 | 1847 | 2019 |
| Connecting the dots: Multivariate time series forecasting with graph neural networks Z Wu, S Pan, G Long, J Jiang, X Chang, C Zhang (KDD-2020) Proceedings of the 26th ACM SIGKDD International Conference on …, 2020 | 1196 | 2020 |
| Adversarially Regularized Graph Autoencoder for Graph Embedding S Pan, R Hu, G Long, J Jiang, L Yao, C Zhang (IJCAI-2018)The Twenty-Seventh International Joint Conference on Artificial …, 2018 | 971 | 2018 |
| DiSAN: Directional Self-Attention Network for RNN/CNN-free Language Understanding Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang (AAAI-2018) The Thirty-Second AAAI Conference on Artificial Intelligence …, 2018 | 859* | 2018 |
| Attributed Graph Clustering: A Deep Attentional Embedding Approach C Wang, S Pan, R Hu, G Long, J Jiang, C Zhang (IJCAI-2019) the Twenty-Eighth International Joint Conference on Artificial …, 2019 | 488 | 2019 |
| Mgae: Marginalized graph autoencoder for graph clustering C Wang, S Pan, G Long, X Zhu, J Jiang (CIKM-2017) the 2017 ACM on Conference on Information and Knowledge …, 2017 | 458 | 2017 |
| Fedproto: Federated prototype learning across heterogeneous clients Y Tan, G Long, L Liu, T Zhou, Q Lu, J Jiang, C Zhang Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8432-8440, 2022 | 316 | 2022 |
| Learning graph embedding with adversarial training methods S Pan, R Hu, S Fung, G Long, J Jiang, C Zhang (TCYB) IEEE transactions on Cybernetics 50 (6), 2475--2487, 2020 | 307 | 2020 |
| Federated learning for open banking G Long, Y Tan, J Jiang, C Zhang (Book Chapter) Federated learning, 240-254, 2020 | 248 | 2020 |
| Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification W Tang, G Long, L Liu, T Zhou, M Blumenstein, J Jiang (ICLR-2022) International Conference on Learning Representations 2022, 1-17, 2021 | 225* | 2021 |
| Optimal cloud resource auto-scaling for web applications J Jiang, J Lu, G Zhang, G Long (CCGrid-2013)13th IEEE/ACM International Symposium on Cluster, Cloud, and …, 2013 | 201 | 2013 |
| Bi-directional block self-attention for fast and memory-efficient sequence modeling T Shen, T Zhou, G Long, J Jiang, C Zhang (ICLR-2018) 6th International Conference on Learning Representations, 2018 | 178 | 2018 |
| Learning Private Neural Language Modeling with Attentive Aggregation S Ji, S Pan, G Long, X Li, J Jiang, Z Huang (IJCNN-2019) International Joint Conference on Neural Networks, 2019 2019, 1-8, 2019 | 159 | 2019 |
| Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang (IJCAI-2018)The Twenty-Seventh International Joint Conference on Artificial …, 2018 | 152* | 2018 |
| A universal representation transformer layer for few-shot image classification L Liu, W Hamilton, G Long, J Jiang, H Larochelle (ICLR-2021) International Conference on Learning Representations 2021 2021, 1-11, 2021 | 136 | 2021 |
| Scaling-up item-based collaborative filtering recommendation algorithm based on hadoop J Jiang, J Lu, G Zhang, G Long (SERVICES -2011) IEEE World Congress on Services, 2011, 490-497, 2011 | 136 | 2011 |
| Multi-center federated learning: clients clustering for better personalization G Long, M Xie, T Shen, T Zhou, X Wang, J Jiang World Wide Web 26 (1), 481-500, 2022 | 121 | 2022 |
| Federated Learning from Pre-Trained Models: A Contrastive Learning Approach Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang (NeurIPS-22) Thirty-sixth Conference on Neural Information Processing …, 2022 | 111 | 2022 |
| Learning to propagate for graph meta-learning L Liu, T Zhou, G Long, J Jiang, C Zhang (NeurIPS-2019) 33rd Conference on Neural Information Processing Systems …, 2019 | 100 | 2019 |
| Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction Y Li, G Long, T Shen, T Zhou, L Yao, H Huo, J Jiang (AAAI-2020) The AAAI Conference on Artificial Intelligence, 2020 | 94 | 2020 |
Guodong LongAssociate Professor, Faculty of Engineering and IT, University of Technology Sydney在 uts.edu.au 的电子邮件经过验证
