Background: Graph Neural Networks

  • Graph neural networks (GNNs) are rapidly advancing progress in ML for complex graph data applications. I’ve composed this concise recipe dedicated to students who are lookin to learn and keep up-to-date with GNNs. It’s non-exhaustive but it aims to get students familiar with the topic.

Gentle Introduction to GNNs

Survey Papers on GNNs

  • Here are two fantastic survey papers on the topic to get a broader and concise picture of GNNs and recent progress:

Diving Deep into GNNs

GNN Papers and Implementations

  • If you want to keep up-to-date with popular recent methods and paper implementations for GNNs, the Papers with Code community maintains this useful collection:

Benchmarks and Datasets

Tools

Citation

If you found our work useful, please cite it as:

@article{Chadha2020DistilledGraphNeuralNetworks,
  title   = {Graph Neural Networks},
  author  = {Chadha, Aman},
  journal = {Distilled AI},
  year    = {2020},
  note    = {\url{https://aman.ai}}
}