https://github.com/neurodata/goat

A paper (in progress) on graph matching via optimal transport. On arxiv at https://arxiv.org/abs/2111.05366
https://github.com/neurodata/goat

graph-algorithms graph-alignment graphs networks python statistics

Last synced: 3 days ago
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A paper (in progress) on graph matching via optimal transport. On arxiv at https://arxiv.org/abs/2111.05366

• Host: GitHub
• URL: https://github.com/neurodata/goat
• Owner: neurodata
• License: mit
• Created: 2021-03-01T20:13:08.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-12-14T20:36:02.000Z (almost 3 years ago)
• Last Synced: 2023-03-11T22:07:40.305Z (over 1 year ago)
• Topics: graph-algorithms, graph-alignment, graphs, networks, python, statistics
• Language: Python
• Homepage: http://docs.neurodata.io/goat/
• Size: 33.2 MB
• Stars: 8
• Watchers: 2
• Forks: 3
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# GOAT

A paper using optimal transport to solve the graph matching problem.

https://arxiv.org/abs/2111.05366

## Repo structure 

- ``.github``: Files specifying how the repo behaves on GitHub

- ``data``: Directory to store the raw data. 

- ``docs``: Files to build the documentation website in the form of a [Jupyter Book](https://jupyterbook.org/intro.html)

- ``pkg``: A local Python package used for analysis in the Jupyter Notebooks

## Building the book 

*Coming soon*

## Running the code

*Coming soon*

## Credits

This project is created using the excellent open source [Jupyter Book project](https://jupyterbook.org/) and the [executablebooks/cookiecutter-jupyter-book template](https://github.com/executablebooks/cookiecutter-jupyter-book).