Define a custom loss function:

```
import keras.backend as K
def euclidean_distance_loss(y_true, y_pred):
"""
Euclidean distance loss
https://en.wikipedia.org/wiki/Euclidean_distance
:param y_true: TensorFlow/Theano tensor
:param y_pred: TensorFlow/Theano tensor of the same shape as y_true
:return: float
"""
return K.sqrt(K.sum(K.square(y_pred - y_true), axis=-1))
```

Use it:

```
model.compile(loss=euclidean_distance_loss, optimizer='rmsprop')
```