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jingleheimer
This code is really good.
Lorkki
Though, in the finest academic tradition, once you try to actually run it, you'll find that it silently depends on a separate library written by the author, which you'll have to find yourself.

(In this case "tensorcv", which is in a separate repository: https://github.com/conan7882/DeepVision-tensorflow )

That aside, I agree that it's an easier read than most ML code.

conan7882
I though I have removed all the dependency on 'tensorcv'. It turns out I forgot the dataflow part. Now it should be run without 'tensorcv'. Thanks for pointing out.
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?

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?
amelius
Question: what framework is used mostly by academic researchers these days for DL?
nabla9
Tensorflow, although PyTorch is gaining popularity.
amelius
Ok. I guess in this case the authors used TF because three of the authors work at Google.