diff options
author | Rémi Flamary <remi.flamary@gmail.com> | 2017-09-14 16:22:41 +0200 |
---|---|---|
committer | GitHub <noreply@github.com> | 2017-09-14 16:22:41 +0200 |
commit | e70d5420204db78691af2d0fbe04cc3d4416a8f4 (patch) | |
tree | f11601b6b1d7ef821a0ae3233960f6f29a1ac0f7 /README.md | |
parent | a53ede95f916a11e2150ab7917820d813c0034bc (diff) | |
parent | c7eef9dd32212ddeebf716cd5dd54df8974c166d (diff) |
Merge pull request #23 from rflamary/gromov
Gromov-Wasserstein distance
Diffstat (limited to 'README.md')
-rw-r--r-- | README.md | 4 |
1 files changed, 3 insertions, 1 deletions
@@ -16,7 +16,7 @@ It provides the following solvers: * Conditional gradient [6] and Generalized conditional gradient for regularized OT [7]. * Joint OT matrix and mapping estimation [8]. * Wasserstein Discriminant Analysis [11] (requires autograd + pymanopt). - +* Gromov-Wasserstein distances and barycenters [12] Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder. @@ -184,3 +184,5 @@ You can also post bug reports and feature requests in Github issues. Make sure t [10] Chizat, L., Peyré, G., Schmitzer, B., & Vialard, F. X. (2016). [Scaling algorithms for unbalanced transport problems](https://arxiv.org/pdf/1607.05816.pdf). arXiv preprint arXiv:1607.05816. [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. |