Implementation of simple autoencoders networks with Keras
Autoencoders (AE) are neural networks that aims to copy their inputs to their outputs. They work by compressing the input into a latent-space representation, and then reconstructing the output from this representation. This kind of network is composed of two parts :
This notebook show the implementation of five types of autoencoders :
The explanation of each (except VAE) can be found here