yueliu1999/Awesome-Deep-Graph-Clustering
A curated repository of state-of-the-art deep graph clustering methods including research papers, code implementations, and benchmark datasets.
Not currently ranked — collecting fresh signals.
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This repository aggregates deep learning methods for graph clustering, which aims to partition nodes in graph structures into meaningful groups. It covers graph neural networks, graph convolutional networks, self-supervised learning approaches, and related techniques. The collection includes published papers, accompanying code implementations, and datasets used for benchmarking clustering performance on graph data.
Frequently asked
- What is yueliu1999/Awesome-Deep-Graph-Clustering?
- A curated repository of state-of-the-art deep graph clustering methods including research papers, code implementations, and benchmark datasets.
- Is Awesome-Deep-Graph-Clustering open source?
- Yes — yueliu1999/Awesome-Deep-Graph-Clustering is open source, released under the MIT license.
- What language is Awesome-Deep-Graph-Clustering written in?
- yueliu1999/Awesome-Deep-Graph-Clustering is primarily written in Python.
- How popular is Awesome-Deep-Graph-Clustering?
- yueliu1999/Awesome-Deep-Graph-Clustering has 1k stars on GitHub.
- Where can I find Awesome-Deep-Graph-Clustering?
- yueliu1999/Awesome-Deep-Graph-Clustering is on GitHub at https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering.