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Here is the implementation from this episode: github.com/manicman1999/Matchue-More-with-LessEnjoy!
Great work a-GAN, Matt! Very helpful.
isnt Gradient Penalty used for enforcing Lipschitz Continuity?
I thought Matchue GAN was a type of GAN I left out...actually googled it!
great video!maybe you could have shown images from the same architecture minus some augmentation methods?but then again from the small sample size of plotting just a tiny range for comparison maybe it wouldnt have been reflective of the difference
Here is the implementation from this episode: github.com/manicman1999/Matchue-More-with-Less
Enjoy!
Great work a-GAN, Matt! Very helpful.
isnt Gradient Penalty used for enforcing Lipschitz Continuity?
I thought Matchue GAN was a type of GAN I left out...actually googled it!
great video!
maybe you could have shown images from the same architecture minus some augmentation methods?
but then again from the small sample size of plotting just a tiny range for comparison maybe it wouldnt have been reflective of the difference