diff --git a/jax_privacy/matrix_factorization/toeplitz.py b/jax_privacy/matrix_factorization/toeplitz.py
index 61cb0839..eb530030 100644
--- a/jax_privacy/matrix_factorization/toeplitz.py
+++ b/jax_privacy/matrix_factorization/toeplitz.py
@@ -177,16 +177,14 @@ def materialize_lower_triangular(
 ) -> jax.Array:
   """Creates a lower-triangular Toeplitz matrix.
 
-   Example: If `coef = [a, b, c]` and `n = 6`, then this method returns:
+  Example: If ``coef = [a, b, c]`` and ``n = 6``, then this method returns::
 
-  ```
-  [a 0 0 0 0 0]
-  [b a 0 0 0 0]
-  [c b a 0 0 0]
-  [0 c b a 0 0]
-  [0 0 c b a 0]
-  [0 0 0 c b a]
-  ```
+    [a 0 0 0 0 0]
+    [b a 0 0 0 0]
+    [c b a 0 0 0]
+    [0 c b a 0 0]
+    [0 0 c b a 0]
+    [0 0 0 c b a]
 
   Args:
     coef: The nonzero coefficients of a lower-triangular Toeplitz matrix C, that
@@ -211,16 +209,15 @@ def solve_banded(coef: jax.Array, rhs: jax.Array) -> jax.Array:
   Note we want to be able to back-propagate gradients through this function,
   hence we cannot use scipy.linalg.solve_toeplitz.
 
-  Example: coef = [a, b, c], rhs = [1, 1, 1, 1, 1, 1], we solve the following
-  system for x
-  ```
-  [a 0 0 0 0 0] [x_0]   [1]
-  [b a 0 0 0 0] [x_1]   [1]
-  [c b a 0 0 0] [x_2] = [1]
-  [0 c b a 0 0] [x_3]   [1]
-  [0 0 c b a 0] [x_4]   [1]
-  [0 0 0 c b a] [x_5]   [1]
-  ```
+  Example: ``coef = [a, b, c]``, ``rhs = [1, 1, 1, 1, 1, 1]``, we solve the
+  following system for x::
+
+    [a 0 0 0 0 0] [x_0]   [1]
+    [b a 0 0 0 0] [x_1]   [1]
+    [c b a 0 0 0] [x_2] = [1]
+    [0 c b a 0 0] [x_3]   [1]
+    [0 0 c b a 0] [x_4]   [1]
+    [0 0 0 c b a] [x_5]   [1]
 
   Args:
     coef: The nonzero coefficients of a lower-triangular Toeplitz matrix C, that