AtomicGraphNets.jl

AtomicGraphNets.jl implements graph-based models for machine learning on atomic systems, such as Crystal Graph Convolutional Neural Nets, in Julia. It makes use of the Flux ecosystem for model building and the JuliaGraphs ecosystem for graph representation and visualization, as well as adapting some features from GeometricFlux.

Documentation is in progress at the wiki!

Getting Started

1. Clone this package to wherever you want to play.

2. Go and try out the example in examples/example1/ – it has its own README file with detailed instructions.

Future plans

• make docs
• more network architectures (see issues for some ideas)

Contact

Please feel free to fork and play, and reach out here on GitHub or to rkurchin [at] cmu [dot] edu with suggestions, etc.!

Acknowledgements

Many thanks to Dhairya Gandhi for helping out with some adjoints to actually make these layers trainable! :D