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| author | Rémi Flamary <remi.flamary@gmail.com> | 2018-02-15 16:54:23 +0100 |
|---|---|---|
| committer | Rémi Flamary <remi.flamary@gmail.com> | 2018-02-15 16:54:23 +0100 |
| commit | 341a6b55cde2c0826e4c5a558b7507828d01ae08 (patch) | |
| tree | a21be77f96750bcec1d11d76c2a57197b3a916cd /README.md | |
| parent | 71b17f4e956de4503cbdffc2a822bcea18ed85d1 (diff) | |
add documentation
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| -rw-r--r-- | README.md | 2 |
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@@ -200,3 +200,5 @@ You can also post bug reports and feature requests in Github issues. Make sure t [11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016). [Wasserstein Discriminant Analysis](https://arxiv.org/pdf/1608.08063.pdf). arXiv preprint arXiv:1608.08063. [12] Gabriel Peyré, Marco Cuturi, and Justin Solomon, [Gromov-Wasserstein averaging of kernel and distance matrices](http://proceedings.mlr.press/v48/peyre16.html) International Conference on Machine Learning (ICML). 2016. + +[13] Mémoli, Facundo. [Gromov–Wasserstein distances and the metric approach to object matching](https://media.adelaide.edu.au/acvt/Publications/2011/2011-Gromov%E2%80%93Wasserstein%20Distances%20and%20the%20Metric%20Approach%20to%20Object%20Matching.pdf). Foundations of computational mathematics 11.4 (2011): 417-487.
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