2024 |
TPAMI |
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A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun, Kunlun He.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI).
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TMM |
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MGKsite: Multi-Modal Knowledge-Driven Site Selection via Intra and Inter-Modal Graph Fusion
Ke Liang, Lingyuan Meng, Hao Li, Meng Liu, Siwei Wang, Sihang Zhou, Xinwang Liu, Kunlun He.
IEEE Transactions on Multimedia (IEEE TMM).
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ACM MM |
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Simple Yet Effective: Structure Guided Pre-trained Transformer for Multi-modal Knowledge Graph Reasoning
Ke Liang, Lingyuan Meng, Yue Liu, Meng Liu, Wei Wei, Siwei Wang, Suyuan Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu.
The 32st ACM International Conference on Multimedia (ACM MM 24)
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AAAI |
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MINES: Message Intercommunication for Inductive Relation Reasoning Over Neighbor-Enhanced Subgraphs
Ke Liang, Lingyuan Meng, Sihang Zhou, Wenxuan Tu, Siwei Wang, Yue Liu, Meng Liu, Long Zhao, Xiangjun Dong, Xiangjun Dong, Xinwang Liu.
The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)
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AAAI |
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Hawkes-Enhanced Spatial-Temporal Hypergraph Contrastive Learning Based on Criminal Correlations
Ke Liang, Sihang Zhou, Meng Liu, Yue Liu, Wenxuan Tu, Yi Zhang, Liming Fang, Zhe Liu, Xinwang Liu.
The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)
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VLDB |
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Better Learning from Graph Structures: Research on Representation Learning for Knowledge Graph Reasoning
Ke Liang.
The 50th International Conference on Very Large Databases (VLDB 24).
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TKDE |
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FedEAN: Entity-Aware Adversarial Negative Sampling for Federated Knowledge Graph Reasoning
Lingyuan Meng, Ke Liang*, Hao Yu, Yue Liu, Sihang Zhou, Meng Liu, Xinwang Liu.
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE).
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TNNLS |
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SARF: Aliasing Relation-Assisted Self-Supervised Learning for Few-shot Relation Reasoning
Lingyuan Meng, Ke Liang, Bin Xiao, Sihang Zhou, Yue Liu, Meng Liu, Xihong Yang, Xinwang Liu, Jinyan Li.
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
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TNNLS |
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Self-Supervised Temporal Graph Learning with Temporal and Structural Intensity Alignment
Meng Liu, Ke Liang, Yawei Zhao, Wenxuan Tu, Sihang Zhou, Xinbiao Gan, Xinwang Liu, Kunlun He.
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
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CVPR |
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Learn from View Correlation: An Anchor Enhancement Strategy for Multi-view Clustering
Suyuan Liu, Ke Liang, Zhibin Dong, Siwei Wang, Xihong Yang, Sihang Zhou, En Zhu, Xinwang Liu.
The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024).
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BIB |
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Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data
Dayu Hu, Ke Liang, Zhibin Dong, Jun Wang, Yawei Zhao, Kunlun He.
Briefings in Bioinformatics (BIB).
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2023 |
TKDE |
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Knowledge Graph Contrastive Learning based on Relation-Symmetrical Structure
Ke Liang, Yue Liu*, Sihang Zhou, Wenxuan Tu, Yi Wen, Xihong Yang, Xiangjun Dong, Xinwang Liu.
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (ESI Highly Cited Paper)
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SIGIR |
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Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu.
The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)
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PAA |
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ABSLearn: A GNN-based Framework for Aliasing and Buffer-Size Information Retrieval
Ke Liang, Jim Tan*, Dongrui Zeng, Yongzhe Huang, Sharon X. Huang, Gang Tan.
Pattern Analysis and Applications (PAA)
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ACM MM |
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TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification
Meng Liu, Ke Liang*, Dayu Hu, Hao Yu, Yue Liu, Lingyuan Meng, Wenxuan Tu, Sihang Zhou, Xinwang Liu.
The 31st ACM International Conference on Multimedia (ACM MM 2023)
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ACM MM |
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Reinforcement Graph Clustering with Unknown Cluster Number
Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, Stan Z. Li.
The 31st ACM International Conference on Multimedia (ACM MM 2023)
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ICML |
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Dink-Net: Neural Clustering on Large Graphs
Yue Liu, Ke Liang, Xinwang Liu, Jun Xia, Sihang Zhou, Xihong Yang, Stan Z. Li.
The 40th International Conference on Machine Learning (ICML 2023)
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eLife |
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Quantitative Geometry of Blood Cells Extracted from X-Ray Histotomographic Images of Whole Zebrafish
Maksim A. Yakovlev, Ke Liang, Carolyn R. Zaino, Daniel J. Vanselow, Andrew L. Sugarman, Alex Y. Lin, Patrick J. La Riviere, Yuxi Zheng, Justin D. Silverman, John C. Leichty, Sharon X. Huang, Keith C. Cheng
eLife.
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BIB |
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scDFC: A deep fusion clustering method for single-cell RNA-seq data
Dayu Hu, Ke Liang, Sihang Zhou, Wenxuan Tu, Meng Liu, Xinwang Liu.
Briefings in Bioinformatics (BIB)
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2022 |
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A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application
Yue Liu, Jun Xia, Sihang Zhou, Siwei Wang, Xifeng Guo, Xihong Yang, Ke Liang, Wenxuan Tu, Stan Z. Li, Xinwang Liu.
Preprint. Under Review.
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2021 |
PSU |
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Inferring Aliasing and Buffer Size Relationship in C Via Graph Neural Networks
Ke Liang.
Master Thesis
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