Noise#
This layer adds random Gaussian noise to the inputs with a user-defined standard deviation. Noise added to neural network activations acts as a regularizer by indirectly adding a penalty to the weights through the cost function in the output layer.
Parameters#
| # | Name | Default | Type | Description |
|---|---|---|---|---|
| 1 | stddev | 0.1 | float | The standard deviation of the Gaussian noise added to the inputs. |
Example#
use Rubix\ML\NeuralNet\Layers\Noise;
$layer = new Noise(1e-3);
References#
-
C. Gulcehre et al. (2016). Noisy Activation Functions. ↩