Papers Graph Outlier Detection
“Graph Outlier Detection” 태그가 달린 논문 5편 · 필터 해제
A novel robust integrating method by high-order proximity for self-supervised attribute network embedding
Attribute network embedding faces significant challenges, primarily integrating heterogeneous information and managing outliers. In this paper, we introduce a novel Robust Integrating Method by High-order Proximity for S…
AttributeData VisualizationGraph Outlier DetectionLink Prediction+2Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models
A fundamental challenge confronting supervised graph outlier detection algorithms is the prevalent problem of class imbalance, where the scarcity of outlier instances compared to normal instances often results in subopti…
Data AugmentationDenoisingGraph Outlier DetectionOutlier DetectionUnsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method
A large number of studies on Graph Outlier Detection (GOD) have emerged in recent years due to its wide applications, in which Unsupervised Node Outlier Detection (UNOD) on attributed networks is an important area. UNOD …
AttributeGraph Outlier DetectionOutlier DetectionBOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
Detecting which nodes in graphs are outliers is a relatively new machine learning task with numerous applications. Despite the proliferation of algorithms developed in recent years for this task, there has been no standa…
Anomaly DetectionBenchmarkingGraph GenerationGraph Outlier Detection+1PyGOD: A Python Library for Graph Outlier Detection
PyGOD is an open-source Python library for detecting outliers in graph data. As the first comprehensive library of its kind, PyGOD supports a wide array of leading graph-based methods for outlier detection under an easy-…
Graph Outlier Detection