diff --git a/pylearn2/models/dbm/layer.py b/pylearn2/models/dbm/layer.py
index 99a69e5f3c..0c57ab146c 100644
--- a/pylearn2/models/dbm/layer.py
+++ b/pylearn2/models/dbm/layer.py
@@ -1524,7 +1524,7 @@ def __init__(self, n_classes, layer_name, irange = None,
         assert isinstance(n_classes, py_integer_types)
 
         self.output_space = VectorSpace(n_classes)
-        self.b = sharedX( np.zeros((n_classes,)), name = 'softmax_b')
+        self.b = sharedX( np.zeros((n_classes,)), name=layer_name+'_b')
 
         if self.center:
             b = self.b.get_value()
@@ -1624,7 +1624,7 @@ def set_input_space(self, space):
                         idx = rng.randint(0, self.input_dim)
                     W[idx, i] = rng.randn() * self.sparse_istdev
 
-        self.W = sharedX(W,  'softmax_W' )
+        self.W = sharedX(W,  self.layer_name+'_W' )
 
         self._params = [ self.b, self.W ]
 
diff --git a/pylearn2/models/maxout.py b/pylearn2/models/maxout.py
index 92a2f881b3..d6746d6188 100755
--- a/pylearn2/models/maxout.py
+++ b/pylearn2/models/maxout.py
@@ -1226,14 +1226,14 @@ def handle_pool_shape(idx):
                 partial_sum=self.partial_sum,
                 rng=rng)
         W, = self.transformer.get_params()
-        W.name = 'W'
+        W.name = self.layer_name + '_W'
 
         if self.tied_b:
             self.b = sharedX(np.zeros((self.detector_space.num_channels)) +
                              self.init_bias)
         else:
             self.b = sharedX(self.detector_space.get_origin() + self.init_bias)
-        self.b.name = 'b'
+        self.b.name = self.layer_name + '_b'
 
         logger.info('Input shape: {0}'.format(self.input_space.shape))
         logger.info(self.layer_name +
diff --git a/pylearn2/models/mlp.py b/pylearn2/models/mlp.py
index cfe52b5b5c..5623d0616a 100755
--- a/pylearn2/models/mlp.py
+++ b/pylearn2/models/mlp.py
@@ -1187,7 +1187,7 @@ def __init__(self, n_classes, layer_name, irange=None,
         self.output_space = VectorSpace(n_classes)
         if not no_affine:
             self.b = sharedX(np.zeros((n_classes - self.non_redundant,)),
-                             name='softmax_b')
+                             name=layer_name+'_b')
             if init_bias_target_marginals:
 
                 y = init_bias_target_marginals.y
@@ -1331,7 +1331,7 @@ def set_input_space(self, space):
                             idx = rng.randint(0, self.input_dim)
                         W[idx, i] = rng.randn()
 
-            self.W = sharedX(W,  'softmax_W')
+            self.W = sharedX(W,  self.layer_name+'_W')
 
             self._params = [self.b, self.W]
 
diff --git a/pylearn2/scripts/tutorials/convolutional_network/convolutional_network.ipynb b/pylearn2/scripts/tutorials/convolutional_network/convolutional_network.ipynb
index 26e0d079ac..cccd921a27 100644
--- a/pylearn2/scripts/tutorials/convolutional_network/convolutional_network.ipynb
+++ b/pylearn2/scripts/tutorials/convolutional_network/convolutional_network.ipynb
@@ -229,7 +229,7 @@
         "                     max_kernel_norm: 1.9365\n",
         "                 }, !obj:pylearn2.models.mlp.Softmax {\n",
         "                     max_col_norm: 1.9365,\n",
-        "                     layer_name: 'y',\n",
+        "                     layer_name: 'softmax',\n",
         "                     n_classes: 10,\n",
         "                     istdev: .05\n",
         "                 }\n",
diff --git a/pylearn2/scripts/tutorials/jobman_integration.ipynb b/pylearn2/scripts/tutorials/jobman_integration.ipynb
index d5ab14d692..fe65e917ad 100644
--- a/pylearn2/scripts/tutorials/jobman_integration.ipynb
+++ b/pylearn2/scripts/tutorials/jobman_integration.ipynb
@@ -40,7 +40,7 @@
       "                dim: 500,\n",
       "                sparse_init: 15,\n",
       "            }, !obj:pylearn2.models.mlp.Softmax {\n",
-      "                layer_name: 'y',\n",
+      "                layer_name: 'softmax',\n",
       "                n_classes: 10,\n",
       "                irange: 0.\n",
       "            }\n",
@@ -100,7 +100,7 @@
       "                dim: 500,\n",
       "                sparse_init: 15,\n",
       "            }, !obj:pylearn2.models.mlp.Softmax {\n",
-      "                layer_name: 'y',\n",
+      "                layer_name: 'softmax',\n",
       "                n_classes: 10,\n",
       "                irange: 0.\n",
       "            }\n",
diff --git a/pylearn2/scripts/tutorials/multilayer_perceptron/multilayer_perceptron.ipynb b/pylearn2/scripts/tutorials/multilayer_perceptron/multilayer_perceptron.ipynb
index 395be48a9b..6edeb433ab 100644
--- a/pylearn2/scripts/tutorials/multilayer_perceptron/multilayer_perceptron.ipynb
+++ b/pylearn2/scripts/tutorials/multilayer_perceptron/multilayer_perceptron.ipynb
@@ -213,7 +213,7 @@
         "                     dim: 500,\n",
         "                     sparse_init: 15,\n",
         "                 }, !obj:pylearn2.models.mlp.Softmax {\n",
-        "                     layer_name: 'y',\n",
+        "                     layer_name: 'softmax',\n",
         "                     n_classes: 10,\n",
         "                     irange: 0.\n",
         "                 }\n",
@@ -25405,7 +25405,7 @@
         "                     dim: 1000,\n",
         "                     sparse_init: 15\n",
         "                 }, !obj:pylearn2.models.mlp.Softmax {\n",
-        "                     layer_name: 'y',\n",
+        "                     layer_name: 'softmax',\n",
         "                     n_classes: 10,\n",
         "                     irange: 0.\n",
         "                 }\n",
@@ -56634,7 +56634,7 @@
         "                     dim: 500,\n",
         "                     sparse_init: 15\n",
         "                 }, !obj:pylearn2.models.mlp.Softmax {\n",
-        "                     layer_name: 'y',\n",
+        "                     layer_name: 'softmax',\n",
         "                     n_classes: 10,\n",
         "                     irange: 0.\n",
         "                 }\n",
diff --git a/pylearn2/scripts/tutorials/stacked_autoencoders/stacked_autoencoders.ipynb b/pylearn2/scripts/tutorials/stacked_autoencoders/stacked_autoencoders.ipynb
index f2fe0af4df..49d9cd6590 100644
--- a/pylearn2/scripts/tutorials/stacked_autoencoders/stacked_autoencoders.ipynb
+++ b/pylearn2/scripts/tutorials/stacked_autoencoders/stacked_autoencoders.ipynb
@@ -1989,7 +1989,7 @@
         "                 },\n",
         "                 !obj:pylearn2.models.mlp.Softmax {\n",
         "                     max_col_norm: 1.9365,\n",
-        "                     layer_name: 'y',\n",
+        "                     layer_name: 'softmax',\n",
         "                     n_classes: 10,\n",
         "                     irange: .005\n",
         "                 }\n",