ChunjingXiao/ConGNN
Controlled graph neural networks with denoising diffusion for anomaly detection, Expert Systems with Applications 2023
This project helps researchers and data scientists identify unusual patterns or outliers within complex, interconnected datasets. It takes structured graph data, such as citation networks or social graphs, and outputs a list of anomalies. This tool is for anyone working with interconnected data who needs to detect fraud, identify misinformation, or spot unusual system behavior.
No commits in the last 6 months.
Use this if you need to find anomalies in datasets where data points are related to each other, like in a network or graph.
Not ideal if your data is unstructured, purely tabular without meaningful connections, or if you need real-time anomaly detection with extremely low latency.
Stars
9
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jan 06, 2024
Commits (30d)
0
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