Видео с ютуба Deep Graph Learning Foundations

[Deep Graph Learning] 5.4 Graph Isomorphism Network Expressive nets

[Deep Graph Learning] 5.3 GNN expressiveness

[Deep Graph Learning] 5.2 Node permutation equivariance in GNNs

[Deep Graph Learning] 3.5 Global and local aggregation methods

[Deep Graph Learning] 3.3 Graph pooling & embedding aggregation

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

[Deep Graph Learning] 3.1 GCN training and loss optimization

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

[Deep Graph Learning] 2.4 Analyzing a single GCN layer

[Deep Graph Learning] 2.3 Shallow graph node embedding

[Deep Graph Learning] 2.2 The evolving landscape of feature embedding

[Deep Graph Learning] 2.1 The logic behind graph-based learning

[Deep Graph Learning] 1.3 Graph learning tasks (node, edge and graph based)

[Deep Graph Learning] 1.2 The graph matrix: from topology to resilience

[Deep Graph Learning] 1.1 Graph types

KDD 2020: Lecture Style Tutorials: Deep Graph Learning Foundations, Advances and Applications