Reproducibility materials for "Importance of Kernel Bandwidth in Quantum Machine Learning"

Repo structure:

• code contains Python scripts used to generate the data
• reproduce-figures contains Jupyter notebooks that generate the figures in the paper
• data contains the datasets used

Requirements

Easiest way to reproduce my set up is to install anaconda3 and run

conda env create -f environment.yml

Obtaining raw data

Full raw data can be downloaded here (~23GB): https://web.cels.anl.gov/~rshaydulin/results.zip

To reproduce figures, you have to first download the data (results.zip) and unzip it into data folder.