From efdbf9e4fe9295fb1bec893e8aaa9102537cb7f5 Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 16 Feb 2018 14:14:08 +0100
Subject: update doc index

---
 docs/source/readme.rst | 24 ++++++++++++++++++++++++
 1 file changed, 24 insertions(+)

diff --git a/docs/source/readme.rst b/docs/source/readme.rst
index 065093e..514389f 100644
--- a/docs/source/readme.rst
+++ b/docs/source/readme.rst
@@ -172,6 +172,10 @@ want a quick look:
    images <https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping_colors_images.ipynb>`__
 -  `Wasserstein Discriminant
    Analysis <https://github.com/rflamary/POT/blob/master/notebooks/plot_WDA.ipynb>`__
+-  `Gromov
+   Wasserstein <https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov.ipynb>`__
+-  `Gromov Wasserstein
+   Barycenter <https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov_barycenter.ipynb>`__
 
 You can also see the notebooks with `Jupyter
 nbviewer <https://nbviewer.jupyter.org/github/rflamary/POT/tree/master/notebooks/>`__.
@@ -192,6 +196,7 @@ The contributors to this library are:
    Gayraud <https://www.linkedin.com/in/nathalie-t-h-gayraud/?ppe=1>`__
 -  `Stanislas Chambon <https://slasnista.github.io/>`__
 -  `Antoine Rolet <https://arolet.github.io/>`__
+-  Erwan Vautier (Gromov-Wasserstein)
 
 This toolbox benefit a lot from open source research and we would like
 to thank the following persons for providing some code (in various
@@ -204,6 +209,20 @@ languages):
 -  `Marco Cuturi <http://marcocuturi.net/>`__ (Sinkhorn Knopp in
    Matlab/Cuda)
 
+Using and citing the toolbox
+----------------------------
+
+If you use this toolbox in your research and find it useful, please cite
+POT using the following bibtex reference:
+
+::
+
+    @article{flamary2017pot,
+      title={POT Python Optimal Transport library},
+      author={Flamary, R{\'e}mi and Courty, Nicolas},
+      year={2017}
+    }
+
 Contributions and code of conduct
 ---------------------------------
 
@@ -286,6 +305,11 @@ arXiv:1608.08063.
 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.
+
 .. |PyPI version| image:: https://badge.fury.io/py/POT.svg
    :target: https://badge.fury.io/py/POT
 .. |Build Status| image:: https://travis-ci.org/rflamary/POT.svg?branch=master
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