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Performance on Vanilla GAN ?
Did you trying using the Vanilla GAN before using W-GAN ? I tried your approach using Vanilla GAN on toy 2D data and it does not work and wanted to ask whether you faced similar problems.
I did try it. It did work for my toy problem but did not perform well on VGG Faces for example. LS-GAN and standard GANs worked very well on Omniglot.
On Fri, 2 Nov 2018 at 20:36, Debasmit Das [email protected] wrote:
Did you trying using the Vanilla GAN before using W-GAN ? I tried your approach using Vanilla GAN on toy 2D data and it does not work and wanted to ask whether you faced similar problems.
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Thanks for the quick response. I am trying on 2D data with gaussian classes. I am trying to learn from 3 classes and trying generate samples for the 4th class for which only a single sample exists. The results look something like this -
Here the 3 training classes are blue, red and black centered at (-3,3), (3,3,) and (0,0) and I am trying to generate samples from the 4th class using a sample centered at (-3,-3) but it would not generate the correct distribution
Any reason this toy problem won't work ? Less Data or Less no. of classes or anything.