Creating the Heterogeneous (Directed/Uni-Directed) Graphs using DGL

Train a Graph Neural Network for Note Classification Using DGL

[Deep Graph Learning] 1.1 Graph types

[Deep Graph Learning] 3.5 Global and local aggregation methods

[Deep Graph Learning] 5.4 Graph Isomorphism Network Expressive nets

[Deep Graph Learning] 4.2 Batching and GNN sampling methods

[Deep Graph Learning] 3.1 GCN training and loss optimization

[Deep Graph Learning] 2.5 Generalized GCN node and layer updates

Graph and Beyond The Second Course #2.8: Introducing the ArangoDB-DGL Adapter

PyTorch: Node Classification w/ Graph Neural Network on DGL for GCN

[Deep Graph Learning] 3.2 GNN inductive capability & graph-based learning

01 - Graph convolutional network (GCN) explained | step-by-step

[Deep Graph Learning] 2.4 Analyzing a single GCN layer