I would like to build an autoencoder (CNN) to learn a representation of my data.
I never built such a network and I have some experience in supervised learning (classification).
I would like to know if some good practices in training a classifier is also right for an autoencoder:
Does reference architecture exists like ResNet/Inception or something? If not, should I design manually layers?
Does transfer learning/fine tuning works for autoencoder (or is it better to train from scratch)?