diff --git a/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py b/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py
index a1b9b60bb..baa85e741 100644
--- a/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py
+++ b/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py
@@ -95,7 +95,7 @@ def propagate(self, time, sigmapts, modelfct):
             Time :math:`t` which is passed on to the modelfunction.
         sigmapts : np.ndarray, shape=(2 N+1, N)
             Sigma points (N is the spatial dimension of the dynamic model)
-        modelfct : callable, signature=(t, x, **kwargs)
+        modelfct : callable, signature=(t, x, \\**kwargs)
             Function through which to propagate
 
         Returns
diff --git a/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py b/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py
index dee581c99..71c89016d 100644
--- a/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py
+++ b/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py
@@ -25,15 +25,15 @@ class LinearSDEModel(continuousmodel.ContinuousModel):
 
     Parameters
     ----------
-    driftmatrixfct : callable, signature=(t, **kwargs)
+    driftmatrixfct : callable, signature=(t, \\**kwargs)
         This is F = F(t). The evaluations of this function are called
         the drift(matrix) of the SDE.
         Returns np.ndarray with shape=(n, n)
-    forcfct : callable, signature=(t, **kwargs)
+    forcfct : callable, signature=(t, \\**kwargs)
         This is u = u(t). Evaluations of this function are called
         the force(vector) of the SDE.
         Returns np.ndarray with shape=(n,)
-    dispmatrixfct : callable, signature=(t, **kwargs)
+    dispmatrixfct : callable, signature=(t, \\**kwargs)
         This is L = L(t). Evaluations of this function are called
         the dispersion(matrix) of the SDE.
         Returns np.ndarray with shape=(n, s)