yueliu1999/Awesome-Deep-Graph-Clustering
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
This is a curated collection of cutting-edge deep graph clustering methods, ideal for researchers and practitioners working with complex network data. It brings together academic papers, their associated code, and relevant datasets for various approaches to group interconnected items. Anyone looking to divide nodes within a graph structure into meaningful clusters can use this resource.
998 stars. No commits in the last 6 months.
Use this if you are a researcher or data scientist focused on applying or developing advanced deep learning techniques to identify underlying communities or groups within graph-structured data.
Not ideal if you are looking for an out-of-the-box software tool to perform simple graph clustering without engaging with academic research or code implementations.
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998
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152
Language
Python
License
MIT
Category
Last pushed
May 06, 2025
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