Apply additive zero-centered Gaussian noise.

Inherits From: Layer

This is useful to mitigate overfitting (you could see it as a form of random data augmentation). Gaussian Noise (GS) is a natural choice as corruption process for real valued inputs.

As it is a regularization layer, it is only active at training time.

stddev Float, standard deviation of the noise distribution.