120 citations · 205 across the 4 of their papers we have counts for
5 papers
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
Sheng Xiang, Mingzhi Zhu, Dawei Cheng +5
Credit card fraud incurs a considerable cost for both cardholders and issuing banks. Contemporary methods apply machine learning-based classifiers to detect fraudulent behavior fro…
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels
Yayong Li, Jie Yin, Ling Chen
Graph Neural Networks (GNNs) have achieved state-of-the-art results for semi-supervised node classification on graphs. Nevertheless, the challenge of how to effectively learn GNNs…
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation
Rongrong Ma, Guansong Pang, Ling Chen +1
Graph-level anomaly detection (GAD) describes the problem of detecting graphs that are abnormal in their structure and/or the features of their nodes, as compared to other graphs.…
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
Ling Chen, Jun Cui, Xing Tang +4
Although the state-of-the-art traditional representation learning (TRL) models show competitive performance on knowledge graph completion, there is no parameter sharing between the…
Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting
Ling Chen, Jiahui Xu, Binqing Wu +4
The problem of air pollution threatens public health. Air quality forecasting can provide the air quality index hours or even days later, which can help the public to prevent air p…