This code is a supplement to the Tutorial on Variational Autoencoders. It allows you to reproduce the example experiments in the tutorial's later sections. This code contains two demos. The first is a ...

Autoencoders are a type of neural network used for unsupervised learning. They learn to reconstruct input data by encoding it into a lower-dimensional latent space and then decoding it back to the ...

Autoencoders are a class of neural networks that aim to learn efficient representations of input data by encoding and then reconstructing it. They comprise two main parts: the encoder, which ...