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authorMarc Glisse <marc.glisse@inria.fr>2020-02-06 21:54:44 +0100
committerMarc Glisse <marc.glisse@inria.fr>2020-02-06 21:54:44 +0100
commit518c619d578dc6f168b6369417f15872e3cd0056 (patch)
treeb2465664179d72905073d049b043fd6baa5134e9 /src/python/doc/wasserstein_distance_user.rst
parent08b82e8a606a7fcd1219e7074cc2f15340090e59 (diff)
use bibtex
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--- a/src/python/doc/wasserstein_distance_user.rst
+++ b/src/python/doc/wasserstein_distance_user.rst
@@ -13,15 +13,15 @@ Functions
---------
This implementation uses the Python Optimal Transport library and is based on
ideas from "Large Scale Computation of Means and Cluster for Persistence
-Diagrams via Optimal Transport".
+Diagrams via Optimal Transport" :cite:`10.5555/3327546.3327645`.
.. autofunction:: gudhi.wasserstein.wasserstein_distance
This other implementation comes from `Hera
-<https://bitbucket.org/grey_narn/hera/src/master/>`_ (BSD-3-Clause) and is
-based on `"Geometry Helps to Compare Persistence Diagrams."
-<http://dx.doi.org/10.1137/1.9781611974317.9>`_ by Michael Kerber, Dmitriy
-Morozov, and Arnur Nigmetov, at ALENEX 2016.
+<https://bitbucket.org/grey_narn/hera/src/master/>`_ (BSD-3-Clause) which is
+based on "Geometry Helps to Compare Persistence Diagrams"
+:cite:`Kerber:2017:GHC:3047249.3064175` by Michael Kerber, Dmitriy
+Morozov, and Arnur Nigmetov.
.. autofunction:: gudhi.hera.wasserstein_distance