This repository contains the implementation of the paper Sinkhorn Divergences for Unbalanced Optimal Transport in pytorch. If you use this work for your research, please cite the paper:
@article{sejourne2019sinkhorn,
title={Sinkhorn Divergences for Unbalanced Optimal Transport},
author={S{\'e}journ{\'e}, Thibault and Feydy, Jean and Vialard, Fran{\c{c}}ois-Xavier and Trouv{\'e}, Alain and Peyr{\'e}, Gabriel},
journal={arXiv preprint arXiv:1910.12958},
year={2019}
}
This repository allows to compute the entropically regularized optimal transport in both balanced and unbalanced settings, with divergences such as Kullback-Leibler and total variation.
All functionals such as regularized OT, Sinkhorn divergence and maximum mean discrepancy is available in common/functional.py.
See examples/plot_unb_gradient_flows_2D_frame.py for an example.