A survey of knowledge graph reasoning on graph types: Static, dynamic, and multimodal K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu, F Sun IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 101* | 2022 |
Learn from relational correlations and periodic events for temporal knowledge graph reasoning K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu Proceedings of the 46th international ACM SIGIR conference on research and …, 2023 | 39 | 2023 |
Deep Temporal Graph Clustering M Liu, Y Liu, K Liang, W Tu, S Wang, S Zhou, X Liu The 12th International Conference on Learning Representations, 2024 | 32 | 2024 |
Inductive representation learning in temporal networks via mining neighborhood and community influences M Liu, Y Liu Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 31 | 2021 |
Self-supervised temporal graph learning with temporal and structural intensity alignment M Liu, K Liang, Y Zhao, W Tu, S Zhou, X Gan, X Liu, K He IEEE Transactions on Neural Networks and Learning Systems, 2024 | 26 | 2024 |
Structure guided multi-modal pre-trained transformer for knowledge graph reasoning K Liang, S Zhou, Y Liu, L Meng, M Liu, X Liu arXiv preprint arXiv:2307.03591, 2023 | 25 | 2023 |
scDFC: a deep fusion clustering method for single-cell RNA-seq data D Hu, K Liang, S Zhou, W Tu, M Liu, X Liu Briefings in Bioinformatics 24 (4), bbad216, 2023 | 25 | 2023 |
Curriculum contrastive learning for fake news detection J Ma, Y Liu, M Liu, M Han Proceedings of the 31st ACM International Conference on Information …, 2022 | 18 | 2022 |
Embedding temporal networks inductively via mining neighborhood and community influences M Liu, ZW Quan, JM Wu, Y Liu, M Han Applied Intelligence 52 (14), 16069-16088, 2022 | 17 | 2022 |
Embedding global and local influences for dynamic graphs M Liu, J Wu, Y Liu Proceedings of the 31st ACM international conference on information …, 2022 | 17 | 2022 |
Message intercommunication for inductive relation reasoning K Liang, L Meng, S Zhou, S Wang, W Tu, Y Liu, M Liu, X Liu arXiv preprint arXiv:2305.14074, 2023 | 13 | 2023 |
A dynamic heterogeneous graph perception network with time-based mini-batch for information diffusion prediction W Fan, M Liu, Y Liu International Conference on Database Systems for Advanced Applications, 604-612, 2022 | 10 | 2022 |
SARF: Aliasing Relation–Assisted Self-Supervised Learning for Few-Shot Relation Reasoning L Meng, K Liang, B Xiao, S Zhou, Y Liu, M Liu, X Yang, X Liu, J Li IEEE Transactions on Neural Networks and Learning Systems, 2024 | 9 | 2024 |
Tmac: Temporal multi-modal graph learning for acoustic event classification M Liu, K Liang, D Hu, H Yu, Y Liu, L Meng, W Tu, S Zhou, X Liu Proceedings of the 31st ACM International Conference on Multimedia, 3365-3374, 2023 | 9 | 2023 |
Reinforcement graph clustering with unknown cluster number Y Liu, K Liang, J Xia, X Yang, S Zhou, M Liu, X Liu, SZ Li Proceedings of the 31st ACM international conference on multimedia, 3528-3537, 2023 | 9 | 2023 |
Multi-modal transformer for fake news detection P Yang, J Ma, Y Liu, M Liu Mathematical Biosciences and Engineering 20 (8), 14699-14717, 2023 | 7 | 2023 |
SageDy: A novel sampling and aggregating based representation learning approach for dynamic networks J Wu, M Liu, J Fan, Y Liu, M Han Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 6 | 2021 |
GuardFL: Safeguarding Federated Learning Against Backdoor Attacks through Attributed Client Graph Clustering H Yu, C Ma, M Liu, T Du, M Ding, T Xiang, S Ji, X Liu arXiv preprint arXiv:2306.04984, 2023 | 4 | 2023 |
Network representation learning algorithm based on neighborhood influence sequence M Liu, Z Quan, Y Liu Asian Conference on Machine Learning, 609-624, 2020 | 2 | 2020 |
Hawkes-enhanced spatial-temporal hypergraph contrastive learning based on criminal correlations K Liang, S Zhou, M Liu, Y Liu, W Tu, Y Zhang, L Fang, Z Liu, X Liu Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8733-8741, 2024 | 1 | 2024 |