-
Introduction to python, numpy and pandas (Basic operations) Lab sheet,
-
Introduction to graphs using networkx, eignevectors/eigenvalues computation Lab sheet,
-
Dimensionality reduction - Comparison of PCA vs Laplacian Eigenmaps. Lab sheet,
- Classification using Label Propagation Algorithm (LPA) Paper link and Label Spreading Algorithm (LSA) PaperLink. Lab sheet Lab sheet,
- Text classification using error and label propagation (C&S model) research paper. Lab sheet Lab sheet,
- Error and label propagation (C&S - with scaling) Lab sheet,
- Leveraging Cross-Entropy and Supervised Contrastive Loss for classification. Lab sheet,
- Iterative spectral clustering vs K-Means based spectral clustering. Lab sheet,
- Laplacian-Eigenmap-based decoder for link prediction in unirelational graph. Lab sheet,
- Rescal decoder model for graph reconstruction in multi-relational graph. Lab sheet,
- Graph convolutional Networks- Pytorch implementation on Cora dataset. Lab sheet,
- PageRank-with and without teleportation; Lab sheet,
- Non-linear data generation and construction of a similarity graph. Lab sheet,
- Spectral clustering on half moon data, Lab sheet,
- Spectral clustering vs Girvan-Newman clustering, Lab sheet,
- Similarity graph using K-nearest neighbor, Lab sheet,
- Random walk based shallow embedding model implementation Reference (section 3.3), Lab sheet,