# About Graph Neural Networks

For the initial learning about Graph Neural Networks (GNNs), it is better to start with several survey papers: [https://github.com/thunlp/GNNPapers#survey-papers](https://github.com/thunlp/GNNPapers#survey-papers).

To follow up on the latest topics in this field, the GNN workshops in top AI conferences are good choices to be tracked: [https://github.com/naganandy/graph-based-deep-learning-literature#related-workshops](https://github.com/naganandy/graph-based-deep-learning-literature#related-workshops).

For practical implements, two libraries are commonly used in this field: Pytorch Geometric [https://github.com/rusty1s/pytorch\_geometric](https://github.com/rusty1s/pytorch_geometric) and Deep Graph Library [https://github.com/dmlc/dgl](https://github.com/dmlc/dgl).
