AE-VAE-GAN

Try AE,VAE,DCGAM,AEWGAN, VAEDCGAN on brain dataset in Pytorch

1.Dataset

2.Model

3.Results

4.Tricks for training
a.In the Discriminator or Generater/Decoder, uses sigmoid instead of tanh
b.When training the Discriminator, it would be better to freeze Generator weights update and vice verse.
e.g. def free_params(module: nn.Module): for p in module.parameters(): p.requires_grad = True

def frozen_params(module: nn.Module): for p in module.parameters(): p.requires_grad = False

frozen_params(G) free_params(D)

c. The network should be designed deliberately. If too shallow, the image is blurred. If too deep the image is almost black and couldn't see the brain.

4. Summuray
   VAE_DCGAN could help to denoise and the recovered images are also deblured compared to VAE results.