Revert "[WIP] Sliced OT Plans (#757)" (#766)

This reverts commit 07d6bfa.

Author: rflamary

README.md

@@ -72,7 +72,6 @@ POT provides the following generic OT solvers:
 * Fused unbalanced Gromov-Wasserstein [70].
 * [Optimal Transport Barycenters for Generic Costs](https://pythonot.github.io/auto_examples/barycenters/plot_free_support_barycenter_generic_cost.html) [77]
 * [Barycenters between Gaussian Mixture Models](https://pythonot.github.io/auto_examples/barycenters/plot_gmm_barycenter.html) [69, 77]
-* [Sliced Optimal Transport Plans](https://pythonot.github.io/auto_examples/sliced-wasserstein/plot_sliced_plans.html) [82, 83, 84]
 
 POT provides the following Machine Learning related solvers:
 
@@ -450,8 +449,5 @@ Artificial Intelligence.
 
 [81] Xu, H., Luo, D., & Carin, L. (2019). [Scalable Gromov-Wasserstein learning for graph partitioning and matching](https://proceedings.neurips.cc/paper/2019/hash/6e62a992c676f611616097dbea8ea030-Abstract.html). Neural Information Processing Systems (NeurIPS).
 
-[82] Mahey, G., Chapel, L., Gasso, G., Bonet, C., & Courty, N. (2023). [Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics](https://proceedings.neurips.cc/paper_files/paper/2023/hash/6f1346bac8b02f76a631400e2799b24b-Abstract-Conference.html). Advances in Neural Information Processing Systems, 36, 35350–35385.
 
-[83] Tanguy, E., Chapel, L., Delon, J. (2025). [Sliced Optimal Transport Plans](https://arxiv.org/abs/2508.01243) arXiv preprint 2506.03661.
-
-[84] Liu, X., Diaz Martin, R., Bai Y., Shahbazi A., Thorpe M., Aldroubi A., Kolouri, S. (2024). [Expected Sliced Transport Plans](https://openreview.net/forum?id=P7O1Vt1BdU). International Conference on Learning Representations.
+```

RELEASES.md

@@ -1,11 +1,5 @@
 # Releases
 
-## 0.9.7dev
-
-#### New features
-
-- Added Sliced OT plans (PR #757)
-
 ## 0.9.6.post1
 
 *September 2025*

examples/sliced-wasserstein/plot_sliced_plans.py

@@ -58,8 +58,6 @@
     sliced_wasserstein_sphere,
     sliced_wasserstein_sphere_unif,
     linear_sliced_wasserstein_sphere,
-    min_pivot_sliced,
-    expected_sliced,
 )
 from .gromov import (
     gromov_wasserstein,
@@ -111,8 +109,6 @@
     "sliced_wasserstein_distance",
     "sliced_wasserstein_sphere",
     "linear_sliced_wasserstein_sphere",
-    "min_pivot_sliced",
-    "expected_sliced",
     "gromov_wasserstein",
     "gromov_wasserstein2",
     "gromov_barycenters",