This repository contains the code used for my master thesis, which was also used to create the results of the following paper, available in pre-print on arXiv: https://arxiv.org/abs/2104.01437.
For a quick overview, start with the tutorial notebook.
- PyTorch
- NumPy
- Statsmodels
- KDEpy (using FFTKDE for kernel density estimate.)
- Seaborn (alternative for kernel density estimate)
This project is written in Python 3.