pathpyG
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Conversion of notebooks of ML4Nets course
To test whether the functionality needed for the ML4Nets course has been implemented in pathpyG, we should start converting the practice notebooks, which are available here.
- [ ] Week 01: Introduction to python and pathpyG [@IngoScholtes]
- [ ] Week 02: Shortest paths, Components, Spectral Clustering [@IngoScholtes]
- [ ] Week 03: Random Graphs and Molloy-Reed Model [@IngoScholtes]
- [x] Week 04: Stochastic Block Model [@chrisbloecker]
- [x] Week 05: Entropy and Huffman Coding [@chrisbloecker]
- [ ] Week 06: Random Walks and InfoMap [@FranziskHeeg]
- [ ] Week 07: Similarity Scores and Link Prediction [@IngoScholtes]
- [x] Week 08: Dimensionality Reduction and Laplacian Eigenmaps [@VincenzoPerri]
- [ ] Week 09: Logistic Regression and Neural Networks [does not use pathpyG]
- [ ] Week 10: DeepWalk and node2vec [@lisiq]
- [x] Week 11: Graph Neural Networks [@lisiq]