squareRoot3/Rethinking-Anomaly-Detection
"Rethinking Graph Neural Networks for Anomaly Detection" in ICML 2022
This tool helps data scientists and machine learning engineers detect unusual patterns or fraudulent activities within complex, interconnected datasets. It takes in structured data that represents relationships (like social networks or financial transactions) and identifies anomalies that deviate from normal behavior. The primary users are researchers and practitioners working with graph-structured data for anomaly detection tasks.
200 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or data scientist developing and evaluating advanced graph neural network models for anomaly detection.
Not ideal if you are looking for an out-of-the-box solution to apply anomaly detection without deep expertise in graph neural networks or machine learning.
Stars
200
Forks
33
Language
Python
License
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Category
Last pushed
Jun 25, 2024
Commits (30d)
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