diff --git a/RELEASES.md b/RELEASES.md
index 745a7de67..e7a7fe187 100644
--- a/RELEASES.md
+++ b/RELEASES.md
@@ -15,6 +15,7 @@
 - Add version number to the documentation (PR #696)
 - Update doc for default regularization in `ot.unbalanced` sinkhorn solvers (Issue #691, PR #700)
 - Clean documentation for `gromov`, `lp` and `unbalanced` folders (PR #710)
+- Clean references in documentation (PR #722)
 
 ## 0.9.5
 
diff --git a/ot/bregman/_barycenter.py b/ot/bregman/_barycenter.py
index 77f20f87d..89732f9df 100644
--- a/ot/bregman/_barycenter.py
+++ b/ot/bregman/_barycenter.py
@@ -336,6 +336,7 @@ def free_support_sinkhorn_barycenter(
     ot.bregman.sinkhorn : Entropic regularized OT solver
     ot.lp.free_support_barycenter : Barycenter solver based on Linear Programming
 
+
     .. _references-free-support-barycenter:
     References
     ----------
diff --git a/ot/bregman/_sinkhorn.py b/ot/bregman/_sinkhorn.py
index a288830d2..342ba02e8 100644
--- a/ot/bregman/_sinkhorn.py
+++ b/ot/bregman/_sinkhorn.py
@@ -129,10 +129,10 @@ def sinkhorn(
     array([[0.36552929, 0.13447071],
            [0.13447071, 0.36552929]])
 
+
     .. _references-sinkhorn:
     References
     ----------
-
     .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation
         of Optimal Transport, Advances in Neural Information Processing
         Systems (NIPS) 26, 2013
@@ -1460,6 +1460,7 @@ def sinkhorn_epsilon_scaling(
     array([[0.36552929, 0.13447071],
            [0.13447071, 0.36552929]])
 
+
     .. _references-sinkhorn-epsilon-scaling:
     References
     ----------
diff --git a/ot/da.py b/ot/da.py
index 7fce1b7eb..9cf1d39d4 100644
--- a/ot/da.py
+++ b/ot/da.py
@@ -132,13 +132,13 @@ def sinkhorn_lpl1_mm(
     References
     ----------
     .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-       "Optimal Transport for Domain Adaptation," in IEEE
-       Transactions on Pattern Analysis and Machine Intelligence ,
-       vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE
+        Transactions on Pattern Analysis and Machine Intelligence ,
+        vol.PP, no.99, pp.1-1
 
     .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
-       Generalized conditional gradient: analysis of convergence
-       and applications. arXiv preprint arXiv:1510.06567.
+        Generalized conditional gradient: analysis of convergence
+        and applications. arXiv preprint arXiv:1510.06567.
 
     See Also
     --------
@@ -276,12 +276,12 @@ def sinkhorn_l1l2_gl(
     References
     ----------
     .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-       "Optimal Transport for Domain Adaptation," in IEEE Transactions
-       on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE Transactions
+        on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
     .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
-       Generalized conditional gradient: analysis of convergence and
-       applications. arXiv preprint arXiv:1510.06567.
+        Generalized conditional gradient: analysis of convergence and
+        applications. arXiv preprint arXiv:1510.06567.
 
     See Also
     --------
@@ -423,9 +423,9 @@ def emd_laplace(
     References
     ----------
     .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-       "Optimal Transport for Domain Adaptation," in IEEE
-       Transactions on Pattern Analysis and Machine Intelligence,
-       vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE
+        Transactions on Pattern Analysis and Machine Intelligence,
+        vol.PP, no.99, pp.1-1
 
     .. [30] R. Flamary, N. Courty, D. Tuia, A. Rakotomamonjy,
         "Optimal transport with Laplacian regularization: Applications to domain adaptation and shape matching,"
@@ -743,8 +743,8 @@ def transform_labels(self, ys=None):
         References
         ----------
         .. [27] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
-           "Optimal transport for multi-source domain adaptation under target shift",
-           International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
+            "Optimal transport for multi-source domain adaptation under target shift",
+            International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
 
         """
         nx = self.nx
@@ -1073,8 +1073,8 @@ class LinearGWTransport(LinearTransport):
     References
     ----------
     .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-            distances between Gaussian distributions. Journal of Applied Probability,
-            59(4), 1178-1198.
+        distances between Gaussian distributions. Journal of Applied Probability,
+        59(4), 1178-1198.
 
     """
 
@@ -1580,17 +1580,17 @@ class SinkhornLpl1Transport(BaseTransport):
     References
     ----------
     .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-       "Optimal Transport for Domain Adaptation," in IEEE
-       Transactions on Pattern Analysis and Machine Intelligence ,
-       vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE
+        Transactions on Pattern Analysis and Machine Intelligence ,
+        vol.PP, no.99, pp.1-1
 
     .. [2] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
-       Generalized conditional gradient: analysis of convergence
-       and applications. arXiv preprint arXiv:1510.06567.
+        Generalized conditional gradient: analysis of convergence
+        and applications. arXiv preprint arXiv:1510.06567.
 
     .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
-            Regularized discrete optimal transport. SIAM Journal on Imaging
-            Sciences, 7(3), 1853-1882.
+        Regularized discrete optimal transport. SIAM Journal on Imaging
+        Sciences, 7(3), 1853-1882.
     """
 
     def __init__(
@@ -1724,8 +1724,8 @@ class EMDLaplaceTransport(BaseTransport):
     References
     ----------
     .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-           "Optimal Transport for Domain Adaptation," in IEEE Transactions
-           on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE Transactions
+        on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
     .. [2] R. Flamary, N. Courty, D. Tuia, A. Rakotomamonjy,
         "Optimal transport with Laplacian regularization: Applications to domain adaptation and shape matching,"
@@ -1873,13 +1873,13 @@ class SinkhornL1l2Transport(BaseTransport):
     References
     ----------
     .. [1] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy,
-       "Optimal Transport for Domain Adaptation," in IEEE
-       Transactions on Pattern Analysis and Machine Intelligence ,
-       vol.PP, no.99, pp.1-1
+        "Optimal Transport for Domain Adaptation," in IEEE
+        Transactions on Pattern Analysis and Machine Intelligence ,
+        vol.PP, no.99, pp.1-1
 
     .. [2] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015).
-       Generalized conditional gradient: analysis of convergence
-       and applications. arXiv preprint arXiv:1510.06567.
+        Generalized conditional gradient: analysis of convergence
+        and applications. arXiv preprint arXiv:1510.06567.
 
     .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
             Regularized discrete optimal transport. SIAM Journal on Imaging
@@ -2352,14 +2352,13 @@ class JCPOTTransport(BaseTransport):
     References
     ----------
     .. [1] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
-       "Optimal transport for multi-source domain adaptation under target shift",
-       International Conference on Artificial Intelligence and Statistics (AISTATS),
-       vol. 89, p.849-858, 2019.
+        "Optimal transport for multi-source domain adaptation under target shift",
+        International Conference on Artificial Intelligence and Statistics (AISTATS),
+        vol. 89, p.849-858, 2019.
 
     .. [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
-            Regularized discrete optimal transport. SIAM Journal on Imaging
-            Sciences, 7(3), 1853-1882.
-
+        Regularized discrete optimal transport. SIAM Journal on Imaging
+        Sciences, 7(3), 1853-1882.
 
     """
 
@@ -2524,8 +2523,8 @@ def transform_labels(self, ys=None):
         References
         ----------
         .. [27] Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia
-           "Optimal transport for multi-source domain adaptation under target shift",
-           International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
+            "Optimal transport for multi-source domain adaptation under target shift",
+            International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
         """
         nx = self.nx
 
diff --git a/ot/dr.py b/ot/dr.py
index c374c440c..4914e6b84 100644
--- a/ot/dr.py
+++ b/ot/dr.py
@@ -208,7 +208,7 @@ def wda(
     References
     ----------
     .. [11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).
-            Wasserstein Discriminant Analysis. arXiv preprint arXiv:1608.08063.
+        Wasserstein Discriminant Analysis. arXiv preprint arXiv:1608.08063.
     """  # noqa
 
     if sinkhorn_method.lower() == "sinkhorn":
@@ -348,8 +348,8 @@ def projection_robust_wasserstein(
     References
     ----------
     .. [32] Huang, M. , Ma S. & Lai L. (2021).
-            A Riemannian Block Coordinate Descent Method for Computing
-            the Projection Robust Wasserstein Distance, ICML.
+        A Riemannian Block Coordinate Descent Method for Computing
+        the Projection Robust Wasserstein Distance, ICML.
     """  # noqa
 
     # initialization
@@ -489,7 +489,7 @@ def ewca(
     References
     ----------
     .. [52] Collas, A., Vayer, T., Flamary, F., & Breloy, A. (2023).
-            Entropic Wasserstein Component Analysis.
+        Entropic Wasserstein Component Analysis.
     """  # noqa
     n, d = X.shape
     X = X - X.mean(0)
diff --git a/ot/gaussian.py b/ot/gaussian.py
index 002e69fb4..fa74093a2 100644
--- a/ot/gaussian.py
+++ b/ot/gaussian.py
@@ -566,8 +566,8 @@ def gaussian_gromov_wasserstein_distance(Cov_s, Cov_t, log=False):
     References
     ----------
     .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-    distances between Gaussian distributions. Journal of Applied Probability,
-    59(4), 1178-1198.
+        distances between Gaussian distributions. Journal of Applied Probability,
+        59(4), 1178-1198.
     """
 
     nx = get_backend(Cov_s, Cov_t)
@@ -630,8 +630,8 @@ def empirical_gaussian_gromov_wasserstein_distance(xs, xt, ws=None, wt=None, log
     References
     ----------
     .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-    distances between Gaussian distributions. Journal of Applied Probability,
-    59(4), 1178-1198.
+        distances between Gaussian distributions. Journal of Applied Probability,
+        59(4), 1178-1198.
     """
     xs, xt = list_to_array(xs, xt)
     nx = get_backend(xs, xt)
@@ -698,8 +698,8 @@ def gaussian_gromov_wasserstein_mapping(
     References
     ----------
     .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-    distances between Gaussian distributions. Journal of Applied Probability,
-    59(4), 1178-1198.
+        distances between Gaussian distributions. Journal of Applied Probability,
+        59(4), 1178-1198.
     """
 
     nx = get_backend(mu_s, mu_t, Cov_s, Cov_t)
@@ -788,12 +788,13 @@ def empirical_gaussian_gromov_wasserstein_mapping(
     b : (1, dt) array-like
         bias
 
+
     .. _references-empirical_gaussian_gromov_wasserstein_mapping:
     References
     ----------
     .. [57] Delon, J., Desolneux, A., & Salmona, A. (2022). Gromov–Wasserstein
-    distances between Gaussian distributions. Journal of Applied Probability,
-    59(4), 1178-1198.
+        distances between Gaussian distributions. Journal of Applied Probability,
+        59(4), 1178-1198.
     """
 
     xs, xt = list_to_array(xs, xt)
diff --git a/ot/gromov/_gw.py b/ot/gromov/_gw.py
index 1c8de7b20..5a2e2eda9 100644
--- a/ot/gromov/_gw.py
+++ b/ot/gromov/_gw.py
@@ -911,7 +911,6 @@ def solve_gromov_linesearch(
 
 
     .. _references-solve-linesearch:
-
     References
     ----------
     .. [24] Vayer Titouan, Chapel Laetitia, Flamary Rémi, Tavenard Romain and Courty Nicolas
@@ -1293,6 +1292,7 @@ def fgw_barycenters(
         - :math:`(\mathbf{M}_s)_s`: all distance matrices between the feature of the barycenter and the other features :math:`(dist(\mathbf{X}, \mathbf{Y}_s))_s` shape (`N`, `ns`)
         - values used in convergence evaluation.
 
+
     .. _references-fgw-barycenters:
     References
     ----------
diff --git a/ot/gromov/_partial.py b/ot/gromov/_partial.py
index b08f60174..8e8b2a617 100644
--- a/ot/gromov/_partial.py
+++ b/ot/gromov/_partial.py
@@ -611,6 +611,7 @@ def partial_fused_gromov_wasserstein(
     log : dict
         Convergence information and loss.
 
+
     .. _references-partial-gromov-wasserstein:
     References
     ----------
@@ -907,6 +908,7 @@ def partial_fused_gromov_wasserstein2(
     log : dict
         log dictionary returned only if `log` is `True`
 
+
     .. _references-partial-gromov-wasserstein2:
     References
     ----------
diff --git a/ot/gromov/_semirelaxed.py b/ot/gromov/_semirelaxed.py
index 05ad8b25c..8c60b2569 100644
--- a/ot/gromov/_semirelaxed.py
+++ b/ot/gromov/_semirelaxed.py
@@ -474,12 +474,12 @@ def semirelaxed_fused_gromov_wasserstein(
         (ICML). 2019.
 
     .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2022.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2022.
 
     .. [62] H. Van Assel, C. Vincent-Cuaz, T. Vayer, R. Flamary, N. Courty.
-            "Interpolating between Clustering and Dimensionality Reduction with
-            Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
+        "Interpolating between Clustering and Dimensionality Reduction with
+        Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
     """
     arr = [M, C1, C2]
     if p is not None:
@@ -688,12 +688,12 @@ def semirelaxed_fused_gromov_wasserstein2(
         (ICML). 2019.
 
     .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2022.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2022.
 
     .. [62] H. Van Assel, C. Vincent-Cuaz, T. Vayer, R. Flamary, N. Courty.
-            "Interpolating between Clustering and Dimensionality Reduction with
-            Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
+        "Interpolating between Clustering and Dimensionality Reduction with
+        Gromov-Wasserstein". NeurIPS 2023 Workshop OTML.
     """
     # partial get_backend as the full one will be handled in gromov_wasserstein
     nx = get_backend(C1, C2)
@@ -1244,8 +1244,8 @@ def entropic_semirelaxed_fused_gromov_wasserstein(
     References
     ----------
     .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2022.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2022.
     """
     arr = [M, C1, C2]
     if p is not None:
@@ -1437,8 +1437,8 @@ def entropic_semirelaxed_fused_gromov_wasserstein2(
     References
     ----------
     .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2022.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2022.
     """
     T, log_srfgw = entropic_semirelaxed_fused_gromov_wasserstein(
         M,
diff --git a/ot/gromov/_utils.py b/ot/gromov/_utils.py
index 79afaed36..4ae23d41d 100644
--- a/ot/gromov/_utils.py
+++ b/ot/gromov/_utils.py
@@ -428,9 +428,9 @@ def init_matrix_semirelaxed(C1, C2, p, loss_fun="square_loss", nx=None):
         "Gromov-Wasserstein averaging of kernel and distance matrices."
         International Conference on Machine Learning (ICML). 2016.
 
-    .. [48]  Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2022.
+    .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2022.
     """
     if nx is None:
         C1, C2, p = list_to_array(C1, C2, p)
diff --git a/ot/lp/_barycenter_solvers.py b/ot/lp/_barycenter_solvers.py
index 8b64214d9..4779662e9 100644
--- a/ot/lp/_barycenter_solvers.py
+++ b/ot/lp/_barycenter_solvers.py
@@ -227,12 +227,13 @@ def free_support_barycenter(
 
 
     .. _references-free-support-barycenter:
-
     References
     ----------
-    .. [20] Cuturi, Marco, and Arnaud Doucet. "Fast computation of Wasserstein barycenters." International Conference on Machine Learning. 2014.
+    .. [20] Cuturi, Marco, and Arnaud Doucet. "Fast computation of Wasserstein barycenters."
+        International Conference on Machine Learning. 2014.
 
-    .. [43] Álvarez-Esteban, Pedro C., et al. "A fixed-point approach to barycenters in Wasserstein space." Journal of Mathematical Analysis and Applications 441.2 (2016): 744-762.
+    .. [43] Álvarez-Esteban, Pedro C., et al. "A fixed-point approach to barycenters in Wasserstein space."
+        Journal of Mathematical Analysis and Applications 441.2 (2016): 744-762.
 
     """
 
@@ -369,9 +370,12 @@ def generalized_free_support_barycenter(
     .. _references-generalized-free-support-barycenter:
     References
     ----------
-    .. [20] Cuturi, M. and Doucet, A.. "Fast computation of Wasserstein barycenters." International Conference on Machine Learning. 2014.
+    .. [20] Cuturi, M. and Doucet, A.. "Fast computation of Wasserstein barycenters."
+        International Conference on Machine Learning. 2014.
 
-    .. [42] Delon, J., Gozlan, N., and Saint-Dizier, A.. Generalized Wasserstein barycenters between probability measures living on different subspaces. arXiv preprint arXiv:2105.09755, 2021.
+    .. [42] Delon, J., Gozlan, N., and Saint-Dizier, A.. Generalized Wasserstein barycenters
+        between probability measures living on different subspaces.
+        arXiv preprint arXiv:2105.09755, 2021.
 
     """
     nx = get_backend(*X_list, *a_list, *P_list)
diff --git a/ot/mapping.py b/ot/mapping.py
index 1ec55cb95..ea1917772 100644
--- a/ot/mapping.py
+++ b/ot/mapping.py
@@ -743,8 +743,8 @@ def joint_OT_mapping_kernel(
     References
     ----------
     .. [8] M. Perrot, N. Courty, R. Flamary, A. Habrard,
-       "Mapping estimation for discrete optimal transport",
-       Neural Information Processing Systems (NIPS), 2016.
+        "Mapping estimation for discrete optimal transport",
+        Neural Information Processing Systems (NIPS), 2016.
 
     See Also
     --------
diff --git a/ot/optim.py b/ot/optim.py
index ae8b0ba58..d94200cad 100644
--- a/ot/optim.py
+++ b/ot/optim.py
@@ -287,12 +287,14 @@ def line_search(cost, G, deltaG, Mi, cost_G, df_G, **kwargs):
     .. _references_gcg:
     References
     ----------
+    .. [1] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
+        Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
 
-    .. [1] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
+    .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, "Optimal Transport for Domain Adaptation,"
+        in IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
-    .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, "Optimal Transport for Domain Adaptation," in IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
-
-    .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized conditional gradient: analysis of convergence and applications. arXiv preprint arXiv:1510.06567.
+    .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized conditional gradient:
+        analysis of convergence and applications. arXiv preprint arXiv:1510.06567.
 
     See Also
     --------
@@ -492,8 +494,8 @@ def cg(
     .. _references-cg:
     References
     ----------
-
-    .. [1] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
+    .. [1] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).
+        Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
 
     See Also
     --------
@@ -616,10 +618,9 @@ def semirelaxed_cg(
     .. _references-cg:
     References
     ----------
-
-    .. [48]  Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
-            "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
-            International Conference on Learning Representations (ICLR), 2021.
+    .. [48] Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty.
+        "Semi-relaxed Gromov-Wasserstein divergence and applications on graphs"
+        International Conference on Learning Representations (ICLR), 2021.
 
     """
     if nx is None:
@@ -755,7 +756,6 @@ def partial_cg(
     .. _references-partial-cg:
     References
     ----------
-
     ..  [29] Chapel, L., Alaya, M., Gasso, G. (2020). "Partial Optimal
         Transport with Applications on Positive-Unlabeled Learning".
         NeurIPS.
@@ -885,10 +885,11 @@ def gcg(
     .. _references-gcg:
     References
     ----------
+    .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, "Optimal Transport for Domain Adaptation,"
+        in IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
 
-    .. [5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, "Optimal Transport for Domain Adaptation," in IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
-
-    .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized conditional gradient: analysis of convergence and applications. arXiv preprint arXiv:1510.06567.
+    .. [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized conditional gradient:
+        analysis of convergence and applications. arXiv preprint arXiv:1510.06567.
 
     See Also
     --------
diff --git a/ot/partial.py b/ot/partial.py
index 6b2304e08..f86175b10 100755
--- a/ot/partial.py
+++ b/ot/partial.py
@@ -113,8 +113,8 @@ def partial_wasserstein_lagrange(
     References
     ----------
     .. [28] Caffarelli, L. A., & McCann, R. J. (2010) Free boundaries in
-       optimal transport and Monge-Ampere obstacle problems. Annals of
-       mathematics, 673-730.
+        optimal transport and Monge-Ampere obstacle problems. Annals of
+        mathematics, 673-730.
 
     See Also
     --------
@@ -498,8 +498,8 @@ def entropic_partial_wasserstein(
     References
     ----------
     .. [3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyré, G.
-       (2015). Iterative Bregman projections for regularized transportation
-       problems. SIAM Journal on Scientific Computing, 37(2), A1111-A1138.
+        (2015). Iterative Bregman projections for regularized transportation
+        problems. SIAM Journal on Scientific Computing, 37(2), A1111-A1138.
 
     See Also
     --------
@@ -766,7 +766,7 @@ def partial_gromov_wasserstein(
     .. _references-partial-gromov-wasserstein:
     References
     ----------
-    ..  [29] Chapel, L., Alaya, M., Gasso, G. (2020). "Partial Optimal
+    .. [29] Chapel, L., Alaya, M., Gasso, G. (2020). "Partial Optimal
         Transport with Applications on Positive-Unlabeled Learning".
         NeurIPS.
 
@@ -975,7 +975,7 @@ def partial_gromov_wasserstein2(
     .. _references-partial-gromov-wasserstein2:
     References
     ----------
-    ..  [29] Chapel, L., Alaya, M., Gasso, G. (2020). "Partial Optimal
+    .. [29] Chapel, L., Alaya, M., Gasso, G. (2020). "Partial Optimal
         Transport with Applications on Positive-Unlabeled Learning".
         NeurIPS.
 
@@ -1098,7 +1098,7 @@ def entropic_partial_gromov_wasserstein(
 
     Returns
     -------
-    :math: `gamma` : (dim_a, dim_b) ndarray
+    :math:`gamma` : ndarray, shape (dim_a, dim_b)
         Optimal transportation matrix for the given parameters
     log : dict
         log dictionary returned only if `log` is `True`
diff --git a/ot/smooth.py b/ot/smooth.py
index 266fddd53..9fbac6c73 100644
--- a/ot/smooth.py
+++ b/ot/smooth.py
@@ -576,11 +576,14 @@ def smooth_ot_dual(
     .. _references-smooth-ot-dual:
     References
     ----------
-    .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation of Optimal Transport, Advances in Neural Information Processing Systems (NIPS) 26, 2013
+    .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation of Optimal Transport,
+        Advances in Neural Information Processing Systems (NIPS) 26, 2013
 
-    .. [17] Blondel, M., Seguy, V., & Rolet, A. (2018). Smooth and Sparse Optimal Transport. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS).
+    .. [17] Blondel, M., Seguy, V., & Rolet, A. (2018). Smooth and Sparse Optimal Transport.
+        Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS).
 
-    .. [50] Liu, T., Puigcerver, J., & Blondel, M. (2023). Sparsity-constrained optimal transport. Proceedings of the Eleventh International Conference on Learning Representations (ICLR).
+    .. [50] Liu, T., Puigcerver, J., & Blondel, M. (2023). Sparsity-constrained optimal transport.
+        Proceedings of the Eleventh International Conference on Learning Representations (ICLR).
 
     See Also
     --------
@@ -707,11 +710,14 @@ def smooth_ot_semi_dual(
     .. _references-smooth-ot-semi-dual:
     References
     ----------
-    .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation of Optimal Transport, Advances in Neural Information Processing Systems (NIPS) 26, 2013
+    .. [2] M. Cuturi, Sinkhorn Distances : Lightspeed Computation of Optimal Transport,
+        Advances in Neural Information Processing Systems (NIPS) 26, 2013
 
-    .. [17] Blondel, M., Seguy, V., & Rolet, A. (2018). Smooth and Sparse Optimal Transport. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS).
+    .. [17] Blondel, M., Seguy, V., & Rolet, A. (2018). Smooth and Sparse Optimal Transport.
+        Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS).
 
-    .. [50] Liu, T., Puigcerver, J., & Blondel, M. (2023). Sparsity-constrained optimal transport. Proceedings of the Eleventh International Conference on Learning Representations (ICLR).
+    .. [50] Liu, T., Puigcerver, J., & Blondel, M. (2023). Sparsity-constrained optimal transport.
+        Proceedings of the Eleventh International Conference on Learning Representations (ICLR).
 
     See Also
     --------
diff --git a/ot/stochastic.py b/ot/stochastic.py
index da0639f73..29a8783db 100644
--- a/ot/stochastic.py
+++ b/ot/stochastic.py
@@ -58,10 +58,13 @@ def coordinate_grad_semi_dual(b, M, reg, beta, i):
     -------
     coordinate gradient : ndarray, shape (nt,)
 
+
     .. _references-coordinate-grad-semi-dual:
     References
     ----------
-    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) Stochastic Optimization for Large-scale Optimal Transport. Advances in Neural Information Processing Systems (2016).
+    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016)
+        Stochastic Optimization for Large-scale Optimal Transport.
+        Advances in Neural Information Processing Systems (2016).
     """
     r = M[i, :] - beta
     exp_beta = np.exp(-r / reg) * b
@@ -119,10 +122,13 @@ def sag_entropic_transport(a, b, M, reg, numItermax=10000, lr=None, random_state
     v : ndarray, shape (`nt`,)
         Dual variable.
 
+
     .. _references-sag-entropic-transport:
     References
     ----------
-    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) Stochastic Optimization for Large-scale Optimal Transport. Advances in Neural Information Processing Systems (2016).
+    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016)
+        Stochastic Optimization for Large-scale Optimal Transport.
+        Advances in Neural Information Processing Systems (2016).
     """
 
     if lr is None:
@@ -191,10 +197,13 @@ def averaged_sgd_entropic_transport(
     ave_v : ndarray, shape (`nt`,)
         dual variable
 
+
     .. _references-averaged-sgd-entropic-transport:
     References
     ----------
-    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) Stochastic Optimization for Large-scale Optimal Transport. Advances in Neural Information Processing Systems (2016).
+    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016)
+        Stochastic Optimization for Large-scale Optimal Transport.
+        Advances in Neural Information Processing Systems (2016).
     """
 
     if lr is None:
@@ -250,10 +259,13 @@ def c_transform_entropic(b, M, reg, beta):
     u : ndarray, shape (`ns`,)
         Dual variable.
 
+
     .. _references-c-transform-entropic:
     References
     ----------
-    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) Stochastic Optimization for Large-scale Optimal Transport. Advances in Neural Information Processing Systems (2016).
+    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016)
+        Stochastic Optimization for Large-scale Optimal Transport.
+        Advances in Neural Information Processing Systems (2016).
     """
 
     n_source = np.shape(M)[0]
@@ -325,10 +337,13 @@ def solve_semi_dual_entropic(
     log : dict
         log dictionary return only if log==True in parameters
 
+
     .. _references-solve-semi-dual-entropic:
     References
     ----------
-    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) Stochastic Optimization for Large-scale Optimal Transport. Advances in Neural Information Processing Systems (2016).
+    .. [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016)
+        Stochastic Optimization for Large-scale Optimal Transport.
+        Advances in Neural Information Processing Systems (2016).
     """
 
     if method.lower() == "sag":
@@ -416,10 +431,12 @@ def batch_grad_dual(a, b, M, reg, alpha, beta, batch_size, batch_alpha, batch_be
     grad : ndarray, shape (`ns`,)
         partial grad F
 
+
     .. _references-batch-grad-dual:
     References
     ----------
-    .. [19] Seguy, V., Bhushan Damodaran, B., Flamary, R., Courty, N., Rolet, A.& Blondel, M. Large-scale Optimal Transport and Mapping Estimation. International Conference on Learning Representation (2018)
+    .. [19] Seguy, V., Bhushan Damodaran, B., Flamary, R., Courty, N., Rolet, A.& Blondel, M.
+        Large-scale Optimal Transport and Mapping Estimation. International Conference on Learning Representation (2018)
     """
     G = -(
         np.exp(
diff --git a/ot/unbalanced/_mm.py b/ot/unbalanced/_mm.py
index 47fb1ca7c..0d40f909b 100644
--- a/ot/unbalanced/_mm.py
+++ b/ot/unbalanced/_mm.py
@@ -116,6 +116,7 @@ def mm_unbalanced(
     .. [41] Chapel, L., Flamary, R., Wu, H., Févotte, C., and Gasso, G. (2021).
         Unbalanced optimal transport through non-negative penalized
         linear regression. NeurIPS.
+
     See Also
     --------
     ot.lp.emd : Unregularized OT
diff --git a/ot/unbalanced/_sinkhorn.py b/ot/unbalanced/_sinkhorn.py
index fbb2f8757..d338e1652 100644
--- a/ot/unbalanced/_sinkhorn.py
+++ b/ot/unbalanced/_sinkhorn.py
@@ -141,6 +141,7 @@ def sinkhorn_unbalanced(
     array([[0.3220536, 0.1184769],
            [0.1184769, 0.3220536]])
 
+
     .. _references-sinkhorn-unbalanced:
     References
     ----------
@@ -368,6 +369,7 @@ def sinkhorn_unbalanced2(
     >>> np.round(ot.unbalanced.sinkhorn_unbalanced2(a, b, M, 1., 1.), 8)
     0.19600125
 
+
     .. _references-sinkhorn-unbalanced2:
     References
     ----------
@@ -387,8 +389,8 @@ def sinkhorn_unbalanced2(
         Processing Systems (NIPS) 2015
 
     .. [73] Séjourné, T., Vialard, F. X., & Peyré, G. (2022).
-       Faster unbalanced optimal transport: Translation invariant sinkhorn and 1-d frank-wolfe.
-       In International Conference on Artificial Intelligence and Statistics (pp. 4995-5021). PMLR.
+        Faster unbalanced optimal transport: Translation invariant sinkhorn and 1-d frank-wolfe.
+        In International Conference on Artificial Intelligence and Statistics (pp. 4995-5021). PMLR.
 
     See Also
     --------
@@ -679,6 +681,7 @@ def sinkhorn_knopp_unbalanced(
     array([[0.3220536, 0.1184769],
            [0.1184769, 0.3220536]])
 
+
     .. _references-sinkhorn-knopp-unbalanced:
     References
     ----------
@@ -941,6 +944,7 @@ def sinkhorn_stabilized_unbalanced(
     array([[0.3220536, 0.1184769],
            [0.1184769, 0.3220536]])
 
+
     .. _references-sinkhorn-stabilized-unbalanced:
     References
     ----------
@@ -1219,12 +1223,13 @@ def sinkhorn_unbalanced_translation_invariant(
     array([[0.32205357, 0.11847689],
            [0.11847689, 0.32205357]])
 
+
     .. _references-sinkhorn-unbalanced-translation-invariant:
     References
     ----------
     .. [73] Séjourné, T., Vialard, F. X., & Peyré, G. (2022).
-       Faster unbalanced optimal transport: Translation invariant sinkhorn and 1-d frank-wolfe.
-       In International Conference on Artificial Intelligence and Statistics (pp. 4995-5021). PMLR.
+        Faster unbalanced optimal transport: Translation invariant sinkhorn and 1-d frank-wolfe.
+        In International Conference on Artificial Intelligence and Statistics (pp. 4995-5021). PMLR.
     """
 
     M, a, b = list_to_array(M, a, b)
diff --git a/ot/weak.py b/ot/weak.py
index aa504f7ac..71739605b 100644
--- a/ot/weak.py
+++ b/ot/weak.py
@@ -81,8 +81,8 @@ def weak_optimal_transport(
     References
     ----------
     .. [39] Gozlan, N., Roberto, C., Samson, P. M., & Tetali, P. (2017).
-            Kantorovich duality for general transport costs and applications.
-            Journal of Functional Analysis, 273(11), 3327-3405.
+        Kantorovich duality for general transport costs and applications.
+        Journal of Functional Analysis, 273(11), 3327-3405.
 
     See Also
     --------