FluxML/GeometricFlux.jl

Geometric Deep Learning for Flux

40
/ 100
Emerging

This library helps Julia developers build and train deep learning models on graph-structured data. You provide your graph data, which could be anything from social networks to molecular structures, along with associated features, and the library outputs a trained graph neural network model. It's for machine learning engineers and data scientists who need to perform tasks like node classification, link prediction, or graph classification using specialized deep learning techniques.

355 stars. No commits in the last 6 months.

Use this if you are a Julia developer working with graph-structured data and need to build sophisticated deep learning models that can learn from the relationships and features within your graphs.

Not ideal if you are not a Julia developer or if your data is not inherently graph-based, as it's specifically designed for geometric deep learning applications.

graph-analytics network-science deep-learning machine-learning-engineering data-science
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

355

Forks

29

Language

Julia

License

MIT

Last pushed

Oct 29, 2023

Commits (30d)

0

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