Graph Theory

Graph/GNN courses

1. machine learning with graphs by Stanford, from ML to GNN.

2. Graph deep learning course - graphs, sets, groups, GNNs. youtube

Graph Topics

1. General purpose and community detection GIT karate club bene

2. Connectivity

3. Min-cut: 1, 2, 3, 4, 5, 6

4. Louvain community

5. Girwan newman gist, this worked, this is potentially good too, another, another, another

6. Node2vec, paper, medium1, medium 2 - tutorial - code, git code, original py2 code, taboola code for their medium paper

7. Evaluation metrics for community detection

8. Review for community detection algorithms - paper

9. Term: community structure

10. Term: modularity of networks

11. Unread paper

12. Unread comparison of community detection algos

13. Clustering adjacency matrices

14. Spectral-clustering (is this suppose to be here?)

15. Finding natural groups in undirected graphs

16. Awesome community detection on github

17. Various algorithms

5. Centrality algorithms

1. 5.1. The PageRank algorithm

2. 5.2. The Betweenness Centrality algorithm

3. 5.3. The Closeness Centrality algorithm

4. 5.4. The Degree Centrality algorithm

6. Community detection algorithms

1. 6.1. The Louvain algorithm

2. 6.2. The Label Propagation algorithm

3. 6.3. The Connected Components algorithm

7. Experimental algorithms

1. 7.1. Procedures

2. 7.2. Centrality algorithms

3. 7.3. Community detection algorithms

4. 7.4. Path finding algorithms

5. 7.5. Similarity algorithms

6. 7.6. Link Prediction algorithms

7. 7.7. Preprocessing functions and

Graph Tools

1. Graph-tool is an efficient Python module for manipulation and statistical analysis of graphs

2. NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.