Fractal-based complexity measures for predicting generalization in deep neural networks

Collection of materials for the thesis on generalization in deep neural networks. The tables folder contains CSV files with final tables (granular measures) and Kendall τ correlations by architecture settings. The code folder provides Jupyter notebooks for reading and saving CIFAR-10, used to train and save the models and evaluate the studied complexity measures.