CS224W Review
1.1. Introduction; Structure of graph
Introduction; Structure of graph [작성자 : 신윤종]
2.2. Properties of Networks and Random Graph Models
Network Property, Random Graph Models [작성자 : 이예진]
3.3. Motifs and Structural Roles in Networks
Motifs and Structural Roles in Networks [작성자 : 오진석]
4.4. Community Structure in Networks
Network Community [작성자 : 김태욱]
5.5. Spectral Clustering
Spectral Clustering [작성자 : 정민준]
6.6. Message Passing and Node Classification
Relational Classification, Iterative Classification, Belief Propagation [작성자 : 이재빈]
7.7. Graph Representation Learning
Graph Representation Learning [작성자 : 신민정]
8.8. Graph Neural Networks
Graph Neural Network (GNN), Graph Convolutional Network (GCN), Graph Attention Network (GAT) [작성자 : 이재빈]
9.9. Graph Neural Networks: Hands-on Session
GNN code : PyTorch Geometric [작성자 : 이재빈]
10.10. Deep Generative Model for Graphs
Deep Generative Model for Graphs [작성자 : 신민정]
11.11. Link Analysis: PageRank
Link Analysis: PageRank [작성자 : 신윤종]
12.12. Network Effects and Cascading Behavior
Network Effects and Cascading Behavior [작성자 : 이예진]
13.13. Probabilistic Contagion and Models of Influence
Probabilistic Contagion and Models of Influence [작성자 : 이홍정]
14.14. Influence Maximization in Networks
Influence Maximization in Networks [작성자 : 이홍정]
15.15. Outbreak Detection in Networks
Outbreak Detection in Networks [작성자 : 정민준]
16.16. Network Evolution
Network Evolution [작성자 : 오진석]
17.17. Reasoning over Knowledge Graphs
Reasoning over Knowledge Graph [작성자 : 신윤종]
18.18. Limitations of Graph Neural Networks
Limitations of Graph Neural Networks [작성자 : 김태욱]