[skip ci] reset version for the next one

1 files changed, 16 insertions, 47 deletions

diff --git a/.github/next_release.md b/.github/next_release.md
index 72c55999..64bda353 100644
--- a/.github/next_release.md
+++ b/.github/next_release.md
@@ -1,59 +1,28 @@
-We are pleased to announce the release 3.6.0 of the GUDHI library.
+We are pleased to announce the release 3.7.0 of the GUDHI library.
 
-As a major new feature, the GUDHI library now offers automatic differentiation for the computation of
-persistence diagrams, Cubical complex persistence scikit-learn like interface, datasets fetch methods,
-and weighted version for alpha complex in any dimension D.
+As a major new feature, the GUDHI library now offers ...
 
-Do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). From a user point of view, we recommend to download GUDHI user version (gudhi.3.X.X.tar.gz).
-For further information, please visit the [GUDHI web site](https://gudhi.inria.fr/).
+We are now using GitHub to develop the GUDHI library, do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). From a user point of view, we recommend to download GUDHI user version (gudhi.3.X.X.tar.gz).
 
-# GUDHI 3.6.0 Release Notes
-Below is a list of changes made since GUDHI 3.5.0:
+Below is a list of changes made since GUDHI 3.6.0:
 
-- TensorFlow 2 models that can handle automatic differentiation for the computation of persistence diagrams:
-     - [Cubical complex](https://gudhi.inria.fr/python/latest/cubical_complex_tflow_itf_ref.html)
-     - [lower-star persistence on simplex trees](https://gudhi.inria.fr/python/latest/ls_simplex_tree_tflow_itf_ref.html)
-     - [Rips complex](https://gudhi.inria.fr/python/latest/rips_complex_tflow_itf_ref.html)
+- [Module](link)
+     - ...
 
-- [Cubical complex](https://gudhi.inria.fr/python/latest/cubical_complex_sklearn_itf_ref.html)
-     - Cubical complex persistence scikit-learn like interface
+- [Module](link)
+     - ...
 
-- [Datasets](https://gudhi.inria.fr/python/latest/datasets.html)
-     - `datasets.remote.fetch_bunny` and `datasets.remote.fetch_spiral_2d` allows to fetch datasets from [GUDHI-data](https://github.com/GUDHI/gudhi-data)
-
-- [Alpha complex](https://gudhi.inria.fr/python/latest/alpha_complex_user.html)
-     - python weighted version for alpha complex is now available in any dimension D.
-     - `alpha_complex = gudhi.AlphaComplex(off_file='/data/points/tore3D_300.off')` is deprecated, please use [read_points_from_off_file](https://gudhi.inria.fr/python/latest/point_cloud.html#gudhi.read_points_from_off_file) instead.
-
-- [Edge collapse](https://gudhi.inria.fr/doc/latest/group__edge__collapse.html)
-     - rewriting of the module to improve performance
-
-- [Čech complex](https://gudhi.inria.fr/doc/latest/group__cech__complex.html)
-     - rewriting of the module to improve performance
-
-- [Representations](https://gudhi.inria.fr/python/latest/representations.html#gudhi.representations.vector_methods.BettiCurve)
-     - A more flexible Betti curve class capable of computing exact curves
+- Miscellaneous
+     - The [list of bugs that were solved since GUDHI-3.6.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.7.0+is%3Aclosed) is available on GitHub.
 
-- [C++ documentation](https://gudhi.inria.fr/doc/latest/)
-     - upgrade and improve performance with new doxygen features
+All modules are distributed under the terms of the MIT license.
+However, there are still GPL dependencies for many modules. We invite you to check our [license dedicated web page](https://gudhi.inria.fr/licensing/) for further details.
 
-- [Simplex tree](https://gudhi.inria.fr/python/latest/simplex_tree_ref.html)
-     - `__deepcopy__`, `copy` and copy constructors for python module
-     - `expansion_with_blockers` python interface
+We kindly ask users to cite the GUDHI library as appropriately as possible in their papers, and to mention the use of the GUDHI library on the web pages of their projects using GUDHI and provide us with links to these web pages.
 
-- Installation
-     - Boost ≥ 1.66.0 is now required (was ≥ 1.56.0).
-     - Python >= 3.5 and cython >= 0.27 are now required.
+We provide [bibtex entries](https://gudhi.inria.fr/doc/latest/_citation.html) for the modules of the User and Reference Manual, as well as for publications directly related to the GUDHI library. 
 
-- Miscellaneous
-     - The [list of bugs that were solved since GUDHI-3.5.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.6.0+is%3Aclosed) is available on GitHub.
+Feel free to [contact us](https://gudhi.inria.fr/contact/) in case you have any questions or remarks.
 
-## Contributors
+For further information about downloading and installing the library ([C++](https://gudhi.inria.fr/doc/latest/installation.html) or [Python](https://gudhi.inria.fr/python/latest/installation.html)), please visit the [GUDHI web site](https://gudhi.inria.fr/).
 
-- @albert-github
-- @gspr
-- @Hind-M
-- @MathieuCarriere
-- @mglisse
-- @Soriano-Trigueros
-- @VincentRouvreau