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  :

1. Does reference architecture exists like ResNet/Inception,... ? If not, should I design manually layers  ?

2. Does transfer learning  / fine tuning works for autoencoder (or is it better to train from scratch)  ?

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:

1. Does reference architecture exists like ResNet/Inception or something? If not, should I design manually layers?

2. Does transfer learning/fine tuning works for autoencoder (or is it better to train from scratch)?