G
GraphWaveMachine
benedekrozemberczki/GraphWaveMachine
A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".
★189stars
Python
GPL-3.0
Updated: 8mo ago
📋 Project at a Glance
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What's this?Models project leveraging diffusion and embedding, built with Python, open-source
Who made it?Maintained by benedekrozemberczki team, 189⭐ on GitHub, #2316 out of 3201 in Models
Why does it exist?As the Models landscape evolved, the benedekrozemberczki team identified the need for better diffusion solutions. GraphWaveMachine was created to simplify embedding workflows.
What can it do?Key use cases: factorization, graph-embedding, graph-wavelet
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/benedekrozemberczki/GraphWaveMachine | 官网 https://karateclub.readthedocs.io/
🔗 github.com/benedekrozemberczki/GraphWaveMachine | 官网 https://karateclub.readthedocs.io/
Topics
diffusionembeddingfactorizationgraph-embeddinggraph-waveletgraphwaveheat-kernelkddlaplacianmachine-learningnode2vecrefexrolxspectralstruc2vecstructural-embeddingstructural-roleunsupervised-learningwaveletword2vec