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)?


1 Answer 1


Yes, there are open source examples. Take a look at here and here. About your second question, yes. There are numerous studies. For instance, take a look at Supervised Representation Learning: Transfer Learning with Deep Autoencoders.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.