Zehong-Wang/GPM

Beyond Message Passing: Neural Graph Pattern Machine, ICML 2025

37
/ 100
Emerging

This tool helps researchers and data scientists analyze complex network data by identifying and learning from distinct substructures or patterns within the graph. It takes raw graph data (like social networks, citation networks, or biological networks) and outputs classifications for nodes, predictions for links, or categorizations for entire graphs. Individuals working with graph-structured data in research or advanced analytics would find this useful.

No commits in the last 6 months.

Use this if you need to perform advanced analytics like classifying nodes, predicting relationships, or categorizing entire graphs and believe that individual graph patterns, rather than simple connections, hold crucial information.

Not ideal if you are a business user or practitioner without a strong background in graph neural networks or machine learning, as this is a research-focused development tool.

graph-analytics network-science data-mining machine-learning-research computational-social-science
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

12

Forks

3

Language

Python

License

MIT

Last pushed

May 28, 2025

Commits (30d)

0

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