Appendix

Software

Below, you can find all the libraries that have been used in this course. Feel free to check their documentation for instructions on how to install and use them in your local environment.

• Pytorch Official documentation
• Pytorch examples
• Numpy
• NetworkX

Datasets

Throughout the course, we use the following two different open-source datasets for training our models:

• Cifar10 Dataset
• Open-source graph data from the University of Dortmund

Mathematics

Given below is a list of external links that explain some of the more advanced mathematical terms used.

• Derivatives
• Chain rule
• Probability distributions
• Conditional probabilities
• Expected value
• Kullback–Leibler divergence
• Min-max games
• Singular Value Decomposition
• Eigenvalues and Eigenvectors
• Laplacian matrix
• Chebyshev approximation