Graph neural networks
Graph Neural Networks (GNNs) are neural network architectures that learn on graph-structured data. In recent years, GNN's have rapidly improved in terms of ease-of-implementation and performance, and more success stories being reported. In this post, we will briefly introduce these networks, their development, and the features that have lead to their success.
We will dive deeper into three use-cases, citation networks and drug discovery, using the package Deep graph library (DGL), and e-commerce using Pytorch geometric.Read more