changed VAE sampling variance to 1
diff --git a/examples/variational_autoencoder.py b/examples/variational_autoencoder.py
index be8c51f8890..69b846aab25 100644
--- a/examples/variational_autoencoder.py
+++ b/examples/variational_autoencoder.py
@@ -16,7 +16,7 @@
 latent_dim = 2
 intermediate_dim = 256
 nb_epoch = 50
-epsilon_std = 0.01
+epsilon_std = 1.0
 
 x = Input(batch_shape=(batch_size, original_dim))
 h = Dense(intermediate_dim, activation='relu')(x)
diff --git a/examples/variational_autoencoder_deconv.py b/examples/variational_autoencoder_deconv.py
index 25821eca0d8..1b28a12ef87 100644
--- a/examples/variational_autoencoder_deconv.py
+++ b/examples/variational_autoencoder_deconv.py
@@ -27,7 +27,7 @@
     original_img_size = (img_rows, img_cols, img_chns)
 latent_dim = 2
 intermediate_dim = 128
-epsilon_std = 0.01
+epsilon_std = 1.0
 nb_epoch = 5
 
 x = Input(batch_shape=(batch_size,) + original_img_size)

In discussion with Amar Shah @amarshah.

The loss/negative lower bound is now correct with this fix.
