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authorVincent Rouvreau <vincent.rouvreau@inria.fr>2022-11-14 16:51:11 +0100
committerVincent Rouvreau <vincent.rouvreau@inria.fr>2022-11-14 16:51:11 +0100
commita91160ac15def12eb47dc95fc7c19f26c324c399 (patch)
treeec52db9861de8a136b635a939355b453d6c0671d
parent1deac2baba36201aa4674ce111d17790fff36ef2 (diff)
Update python representations module contributors
-rw-r--r--biblio/how_to_cite_gudhi.bib.in2
-rw-r--r--src/python/doc/representations_sum.inc22
2 files changed, 12 insertions, 12 deletions
diff --git a/biblio/how_to_cite_gudhi.bib.in b/biblio/how_to_cite_gudhi.bib.in
index 71d26a3f..9ddf8405 100644
--- a/biblio/how_to_cite_gudhi.bib.in
+++ b/biblio/how_to_cite_gudhi.bib.in
@@ -222,7 +222,7 @@
}
@incollection{gudhi:PersistenceRepresentationsScikitlearnInterface
-, author = "Mathieu Carri\`ere"
+, author = "Mathieu Carri\`ere, Gard Spreemann, Wojciech Reise"
, title = "Persistence representations scikit-learn like interface"
, publisher = "{GUDHI Editorial Board}"
, edition = "{@GUDHI_VERSION@}"
diff --git a/src/python/doc/representations_sum.inc b/src/python/doc/representations_sum.inc
index 4298aea9..9515f044 100644
--- a/src/python/doc/representations_sum.inc
+++ b/src/python/doc/representations_sum.inc
@@ -1,14 +1,14 @@
.. table::
:widths: 30 40 30
- +------------------------------------------------------------------+----------------------------------------------------------------+-------------------------------------------------------------+
- | .. figure:: | Vectorizations, distances and kernels that work on persistence | :Author: Mathieu Carrière, Martin Royer |
- | img/sklearn-tda.png | diagrams, compatible with scikit-learn. | |
- | | | :Since: GUDHI 3.1.0 |
- | | | |
- | | | :License: MIT |
- | | | |
- | | | :Requires: `Scikit-learn <installation.html#scikit-learn>`_ |
- +------------------------------------------------------------------+----------------------------------------------------------------+-------------------------------------------------------------+
- | * :doc:`representations` |
- +------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------+
+ +------------------------------------------------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+
+ | .. figure:: | Vectorizations, distances and kernels that work on persistence | :Author: Mathieu Carrière, Martin Royer, Gard Spreemann, Wojciech Reise |
+ | img/sklearn-tda.png | diagrams, compatible with scikit-learn. | |
+ | | | :Since: GUDHI 3.1.0 |
+ | | | |
+ | | | :License: MIT |
+ | | | |
+ | | | :Requires: `Scikit-learn <installation.html#scikit-learn>`_ |
+ +------------------------------------------------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+
+ | * :doc:`representations` |
+ +------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------+