diff --git a/pyproject.toml b/pyproject.toml
index 780a39ef7..83c27fae0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -42,7 +42,7 @@ dependencies = [
 	"rdata",
 	"scikit-datasets[cran]>=0.2.2",
 	"scikit-learn>=0.20",
-	"scipy>=1.6.0, <1.14",
+	"scipy>=1.6.0",
 	"typing-extensions",
 ]
 
@@ -64,6 +64,7 @@ test = [
   "pytest",
   "pytest-env",
   "pytest-subtests",
+  "scipy>=1.14", # Changes in sparse array representation.
 ]
 
 [project.urls]
diff --git a/skfda/_utils/_neighbors_base.py b/skfda/_utils/_neighbors_base.py
index 7188d19e4..c6b97bba2 100644
--- a/skfda/_utils/_neighbors_base.py
+++ b/skfda/_utils/_neighbors_base.py
@@ -313,9 +313,12 @@ def kneighbors_graph(
 
             >>> graph = neigh.kneighbors_graph(X[0])
             >>> print(graph)
-                (0, 0)    1.0
-                (0, 8)    1.0
-                (0, 1)    1.0
+            <Compressed Sparse Row sparse matrix of dtype 'float64'
+               with 3 stored elements and shape (1, 30)>
+              Coords    Values
+              (0, 0)    1.0
+              (0, 8)    1.0
+              (0, 1)    1.0
 
         Notes:
             This method wraps the corresponding sklearn routine in the
diff --git a/skfda/representation/irregular.py b/skfda/representation/irregular.py
index e03513a06..07cce5e77 100644
--- a/skfda/representation/irregular.py
+++ b/skfda/representation/irregular.py
@@ -627,7 +627,7 @@ def integrate(
         values_list = np.split(data.values, data.start_indices[1:])
         points_list = np.split(data.points, data.start_indices[1:])
         return np.array([
-            scipy.integrate.simpson(y, x, axis=0)
+            scipy.integrate.simpson(y, x=x, axis=0)
             for y, x in zip(values_list, points_list)
         ])