Convolutional Autoencoder with neural network / deep learning toolbox?

With the neural network toolbox I see how we can stack autoencoders, and how we can create convolutional neural networks, but is there a way within the toolbox to combine the two into a convolutional autoencoder? It seems all the parts are there, but I can't figure out how to put them together.

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Hi, did you find how? I'm looking for the same thing. Thank you
I am also looking for an answer to this question. It is quite trivial to implement AE with convolutional layers in pytorch, here is one example https://github.com/udacity/deep-learning-v2-pytorch/blob/master/autoencoder/convolutional-autoencoder/Convolutional_Autoencoder_Solution.ipynb

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Asked:

on 27 Nov 2018

Commented:

on 30 May 2021

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