2.2k citations · 7.3k across the 84 of their papers we have counts for
29 papers · 1 filter
Knowledge Graph Embedding by Normalizing Flows
Changyi Xiao, Xiangnan He, Yixin Cao
A key to knowledge graph embedding (KGE) is to choose a proper representation space, e.g., point-wise Euclidean space and complex vector space. In this paper, we propose a unified…
Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang, Xiangnan He +3
Graph anomaly detection (GAD) is a challenging binary classification problem due to its different structural distribution between anomalies and normal nodes -- abnormal nodes are a…
Label Denoising through Cross-Model Agreement
Yu Wang, Xin Xin, Zaiqiao Meng +2
Learning from corrupted labels is very common in real-world machine-learning applications. Memorizing such noisy labels could affect the learning of the model, leading to sub-optim…
GIF: A General Graph Unlearning Strategy via Influence Function
Jiancan Wu, Yi Yang, Yuchun Qian +3
With the greater emphasis on privacy and security in our society, the problem of graph unlearning -- revoking the influence of specific data on the trained GNN model, is drawing in…
Weakly Supervised Anomaly Detection: A Survey
Minqi Jiang, Chaochuan Hou, Ao Zheng +6
Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news.…
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion
Wentao Shi, Junkang Wu, Xuezhi Cao +4
Learning hyperbolic embeddings for knowledge graph (KG) has gained increasing attention due to its superiority in capturing hierarchies. However, some important operations in hyper…