フォロー
Yixin Liu
Yixin Liu
Research Fellow, Institute for Integrated and Intelligent Systems (IIIS), Griffith University
確認したメール アドレス: griffith.edu.au - ホームページ
タイトル
引用先
引用先
年
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
6372022
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), 2022
3512022
Graph neural networks for graphs with heterophily: A survey
X Zheng, Y Wang, Y Liu, M Li, M Zhang, D Jin, PS Yu, S Pan
arXiv preprint arXiv:2202.07082, 2022
2662022
Towards unsupervised deep graph structure learning
Y Liu, Y Zheng, D Zhang, H Chen, H Peng, S Pan
ACM Web Conference (WWW), 2022
1932022
Generative and contrastive self-supervised learning for graph anomaly detection
Y Zheng, M Jin, Y Liu, L Chi, KT Phan, YPP Chen
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
1472021
Federated learning on non-iid graphs via structural knowledge sharing
Y Tan, Y Liu, G Long, J Jiang, Q Lu, C Zhang
AAAI Conference on Artificial Intelligence (AAAI), 2023
1332023
Anemone: Graph anomaly detection with multi-scale contrastive learning
M Jin, Y Liu, Y Zheng, L Chi, YF Li, S Pan
ACM International Conference on Information & Knowledge Management (CIKM), 2021
1212021
Anomaly detection in dynamic graphs via transformer
Y Liu, S Pan, YG Wang, F Xiong, L Wang, Q Chen, VCS Lee
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
1112021
Emerging trends in federated learning: From model fusion to federated X learning
S Ji, Y Tan, T Saravirta, Z Yang, Y Liu, L Vasankari, S Pan, G Long, ...
International Journal of Machine Learning and Cybernetics, 2024
792024
Beyond smoothing: Unsupervised graph representation learning with edge heterophily discriminating
Y Liu, Y Zheng, D Zhang, VCS Lee, S Pan
AAAI Conference on Artificial Intelligence (AAAI), 2023
792023
GOOD-D: On unsupervised graph out-of-distribution detection
Y Liu, K Ding, H Liu, S Pan
ACM International Conference on Web Search and Data Mining (WSDM), 2023
622023
Towards self-interpretable graph-level anomaly detection
Y Liu, K Ding, Q Lu, F Li, LY Zhang, S Pan
Advances in Neural Information Processing Systems (NeurIPS), 2023
432023
Learning strong graph neural networks with weak information
Y Liu, K Ding, J Wang, V Lee, H Liu, S Pan
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
422023
Towards data-centric graph machine learning: Review and outlook
X Zheng, Y Liu, Z Bao, M Fang, X Hu, AWC Liew, S Pan
arXiv preprint arXiv:2309.10979, 2023
292023
Integrating graphs with large language models: Methods and prospects
S Pan, Y Zheng, Y Liu
IEEE Intelligent Systems, 2024
272024
From unsupervised to few-shot graph anomaly detection: A multi-scale contrastive learning approach
Y Zheng, M Jin, Y Liu, L Chi, KT Phan, YPP Chen
arXiv preprint arXiv:2202.05525, 2022
212022
PREM: A simple yet effective approach for node-level graph anomaly detection
J Pan, Y Liu, Y Zheng, S Pan
IEEE International Conference on Data Mining (ICDM), 2023
142023
MRD-NETS: multi-scale residual networks with dilated convolutions for classification and clustering analysis of spacecraft electrical signal
Y Liu, K Li, Y Zhang, S Song
IEEE Access 7, 171584-171597, 2020
112020
A novel method of hyperspectral data classification based on transfer learning and deep belief network
K Li, M Wang, Y Liu, N Yu, W Lan
Applied Sciences 9 (7), 1379, 2020
112020
Cyclic label propagation for graph semi-supervised learning
Z Li, Y Liu, Z Zhang, S Pan, J Gao, J Bu
World Wide Web, 2022
82022
現在システムで処理を実行できません。しばらくしてからもう一度お試しください。
論文 1–20