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Stanford CS224W: Machine Learning with Graphs (GNN)

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CS224W

Stanford CS224W: Machine Learning with Graphs

Date Lecture Contents
2022. 07. 11. (월) 1 Introduction: Machine Learning for Graphs
2022. 07. 12. (화) 2 Traditional Methods for ML on Graphs
2022. 07. 13. (수) 3
4
Colab 0
Node Embeddings
Link Analysis: PageRank
Colab 0
2022. 07. 14. (목) 5
6
7
Label Propagation for Node Classification
Graph Neural Networks 1: GNN Model
Graph Neural Networks 2: Design Space
2022. 07. 15. (금) 8
9
Applications of Graph Neural Networks
Theory of Graph Neural Networks
2022. 07. 17. (일) 10
11
Knowledge Graph Embeddings
Reasoning over Knowledge Graphs
2022. 07. 18. (월) 12
13
Frequent Subgraph Mining with GNNs
Community Structure in Networks
2022. 07. 19. (화) 14
15
16
Traditional Generative Models for Graphs
Deep Generative Models for Graphs
Advanced Topics on GNNs
2022. 07. 20. (수) 17
Colab 1
Colab 2
Scaling Up GNNs
Colab 1
Colab 2
2022. 07. 21. (목) Colab 2
Colab 3
Colab 2
Colab 3
2022. 07. 22. (금) GNN 논문 읽기 MTGNN - Multivariate Time Series GNN
2022. 07. 23. (토) Colab 3 Colab 3
2022. 07. 24. (일) Colab 4
Colab 5
Colab 4
Colab 5
2022. 07. 25. (월) Colab 5 Colab 5
2022. 07. 26. (화) Colab 5 Colab 5
2022. 08. 01. (월) LA Traffic Predicting LA Traffic with GNN

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