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Scalable python GPU solvers for fused unbalanced gromov-wasserstein optimal transport problems, with routines and examples to align brain data

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Fused Unbalanced Gromov-Wasserstein for Python

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This package implements multiple GPU-compatible PyTorch solvers to the Fused Unbalanced Gromov-Wasserstein optimal transport problem.

This package is under active development. There is no guarantee that the API and solvers won't change in the near future.

Installation

To install this package, make sure you have an up-to-date version of pip.

From PyPI

In a dedicated Python env, run:

pip install fugw

From source

git clone https://github.com/alexisthual/fugw.git
cd fugw

In a dedicated Python env, run:

pip install -e .

Contributors should also install the development dependencies in order to test and automatically format their contributions.

pip install -e ".[dev]"
pre-commit install

Tests run on CPU and GPU, depending on the configuration of your machine. You can run them with:

pytest

Citing this work

If this package was useful to you, please cite it in your work:

@article{Thual-2022-fugw,
  title={Aligning individual brains with Fused Unbalanced Gromov-Wasserstein},
  author={Thual, Alexis and Tran, Huy and Zemskova, Tatiana and Courty, Nicolas and Flamary, Rémi and Dehaene, Stanislas and Thirion, Bertrand},
  publisher={arXiv},
  doi={10.48550/ARXIV.2206.09398},
  url={https://arxiv.org/abs/2206.09398},
  year={2022},
  copyright={Creative Commons Attribution 4.0 International}
}

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Scalable python GPU solvers for fused unbalanced gromov-wasserstein optimal transport problems, with routines and examples to align brain data

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