In a Variational Autoencoders, z cannot be simply sampled from the output of the autoencoder directly since the network would not be differentiable. Instead, we have to sample from a normal distribution who's parameters are the output of the autoencoder, mu and stddev. I So cannot understand how the network isn't differentiable (lets say we take z = mu + srd). So the reparameterization is not clear to me. Any help would be much appreciated!!
Training the Variational Autoencoder After applying the reparameterization trick
deep learning;training;autoencoder