
Tensorflow implementation of Adversarial Autoencoders - conan7882
https://github.com/conan7882/adversarial-autoencoders-tf
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polynomial
For this particular implementation, what are the advantages of using it for
supervised or unsupervised learning? (in general?)

And if it's just being used for the MNIST dataset, is there a particular
reason for using it in one or the other fashion?

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locuscoeruleus
From what I can gather the supervised approach allows you to only learn the
representation for style rather than which digit it is. The only reason to use
one over the other is to demonstrate that it works, I guess?

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amelius
Question: what framework is used mostly by academic researchers these days for
DL?

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nabla9
Tensorflow, although PyTorch is gaining popularity.

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amelius
Ok. I guess in this case the authors used TF because three of the authors work
at Google.

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jingleheimer
This code is really good.

~~~
AstralStorm
And impossible to use thanks to no license information.

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edtruji
MIT License, it was added after your post
[https://github.com/conan7882/adversarial-autoencoders-
tf/blo...](https://github.com/conan7882/adversarial-autoencoders-
tf/blob/master/LICENSE)

