FelixDJC/Awesome-Graph-Anomaly-Detection
A collection of papers for graph anomaly detection, and published algorithms and datasets.
This project is a curated list of research papers, code, and datasets focused on identifying unusual patterns in interconnected data, like social networks, financial transactions, or biological interactions. It helps researchers and data scientists quickly find cutting-edge techniques and resources to detect anomalies. The project takes in academic papers, associated code implementations, and benchmark datasets, and outputs a structured collection for easy discovery.
136 stars. No commits in the last 6 months.
Use this if you are a researcher or data scientist working on identifying unusual behaviors, fraudulent activities, or rare events within complex network data and need to survey existing methods or find resources.
Not ideal if you are an end-user looking for a ready-to-use software tool to detect anomalies in your specific graph data without needing to understand the underlying research.
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Last pushed
Dec 25, 2023
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