NSLab-CUK/Unified-Graph-Transformer

Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and developed by NS Lab @ CUK based on pure PyTorch backend.

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Emerging

This project helps machine learning researchers and practitioners analyze complex graph-structured data by focusing on both immediate connections and broader network patterns. It takes your graph data (like social networks, biological structures, or citation graphs) and processes it to produce improved, unified numerical representations (embeddings) of nodes and graphs. These representations can then be used for tasks like grouping similar nodes, classifying nodes, or classifying entire graphs.

No commits in the last 6 months.

Use this if you are a machine learning researcher or data scientist working with graph data and need to generate highly accurate node or graph embeddings that capture both local and global structural information for downstream tasks.

Not ideal if you are a business user without a technical background in machine learning or if your data is not graph-structured.

graph-analytics network-science node-classification graph-classification data-embedding
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

28

Forks

5

Language

Python

License

MIT

Last pushed

Jul 17, 2025

Commits (30d)

0

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