diff --git a/mlair/model_modules/fully_connected_networks.py b/mlair/model_modules/fully_connected_networks.py
index 313fc837825e108b877b8a48856a26667211764a..940c9846bbaff1a3e3664169cf46de4f177169bc 100644
--- a/mlair/model_modules/fully_connected_networks.py
+++ b/mlair/model_modules/fully_connected_networks.py
@@ -1,7 +1,7 @@
 __author__ = "Lukas Leufen"
 __date__ = '2021-02-'
 
-from functools import reduce
+from functools import reduce, partial
 
 from mlair.model_modules import AbstractModelClass
 from mlair.helpers import select_from_dict
@@ -62,8 +62,8 @@ class FCN(AbstractModelClass):
     on the window_lead_time parameter.
     """
 
-    _activation = {"relu": keras.layers.ReLU(), "tanh": keras.layers.Activation("tanh"),
-                   "sigmoid": keras.layers.Activation("sigmoid")}
+    _activation = {"relu": keras.layers.ReLU, "tanh": partial(keras.layers.Activation, "tanh"),
+                   "sigmoid": partial(keras.layers.Activation, "sigmoid")}
     _optimizer = {"adam": keras.optimizers.adam, "sgd": keras.optimizers.SGD}
     _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad", "momentum", "nesterov"]
 
@@ -125,9 +125,9 @@ class FCN(AbstractModelClass):
         n_layer, n_hidden = self.layer_configuration
         for layer in range(n_layer):
             x_in = keras.layers.Dense(n_hidden)(x_in)
-            x_in = self.activation(x_in)
+            x_in = self.activation()(x_in)
         x_in = keras.layers.Dense(self._output_shape)(x_in)
-        out = self.activation(x_in)
+        out = self.activation()(x_in)
         self.model = keras.Model(inputs=x_input, outputs=[out])
 
     def set_compile_options(self):