Syllabus

Introduction [covered]

Degree distribution, clustering, centrality (betweenness+closeness) [covered]

PageRank, HITS [covered]

Community detection, evaluation [covered]

Knowledge Graphs [covered]

Node embeddings: Deepwalk, LINE, node2vec

GNN and its general framework, Chebnet, GCN, node classification, graph classification

GraphSage, GAT and pooling: gPool, Diffpool, Eigenpool

Attacks on GNNs, applications

BERT and GBERT, Graph LLMs