Metadata-Version: 2.1
Name: cw-torch
Version: 0.4.2
Summary: Implementation of a Cramer-Wold distance in PyTorch
Home-page: https://github.com/EszKnop/cw-torch
Author: EszKnop,
Author-email: eszknop@gmail.com
License: MIT
Keywords: cramerwold cwae lcw autoencoder cramer wold
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch

# Cramer-Wold Distance

## Repository info

This repository contains an implementation of Cramer-Wold Distance in PyTorch, proposed by [Szymon Knop, Przemysław Spurek, Jacek Tabor, Igor Podolak, Marcin Mazur, Stanisław Jastrzębski (2020)](https://jmlr.org/papers/v21/19-560.html).

## PyPI package

Code is distributed as a [PyPI package](https://pypi.org/project/cw-torch/).
To use it in your project you can install it using PIP: `pip install cw-torch`

## License

This implementation is licensed under the MIT License
