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-rw-r--r--examples/backends/plot_sliced_wass_grad_flow_pytorch.py2
-rw-r--r--examples/backends/plot_wass1d_torch.py8
2 files changed, 6 insertions, 4 deletions
diff --git a/examples/backends/plot_sliced_wass_grad_flow_pytorch.py b/examples/backends/plot_sliced_wass_grad_flow_pytorch.py
index 05b9952..cf5d64d 100644
--- a/examples/backends/plot_sliced_wass_grad_flow_pytorch.py
+++ b/examples/backends/plot_sliced_wass_grad_flow_pytorch.py
@@ -27,6 +27,8 @@ Machine Learning (pp. 4104-4113). PMLR.
#
# License: MIT License
+# sphinx_gallery_thumbnail_number = 4
+
# %%
# Loading the data
diff --git a/examples/backends/plot_wass1d_torch.py b/examples/backends/plot_wass1d_torch.py
index 0abdd6d..cd8e2fd 100644
--- a/examples/backends/plot_wass1d_torch.py
+++ b/examples/backends/plot_wass1d_torch.py
@@ -1,9 +1,9 @@
r"""
-=================================
-Wasserstein 1D with PyTorch
-=================================
+=================================================
+Wasserstein 1D (flow and barycenter) with PyTorch
+=================================================
-In this small example, we consider the following minization problem:
+In this small example, we consider the following minimization problem:
.. math::
\mu^* = \min_\mu W(\mu,\nu)