/GraphNeuralNetworks.jl

Graph Neural Networks in Julia

Primary LanguageJuliaMIT LicenseMIT

GraphNeuralNetworks.jl

codecov

GraphNeuralNetworks.jl is a graph neural network library written in Julia and based on the deep learning framework Flux.jl.

Among its features:

  • Implements common graph convolutional layers.
  • Supports computations on batched graphs.
  • Easy to define custom layers.
  • CUDA support.
  • Integration with Graphs.jl.
  • Examples of node, edge, and graph level machine learning tasks.

Installation

GraphNeuralNetworks.jl is a registered Julia package. You can easily install it through the package manager:

pkg> add GraphNeuralNetworks

Usage

Usage examples can be found in the examples folder. Also, make sure to read the documentation for a comprehensive introduction to the library.

Acknowledgments

GraphNeuralNetworks.jl is largely inspired by PyTorch Geometric, Deep Graph Library, and GeometricFlux.jl.