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VAE with variational nested dropout #60

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VAE with variational nested dropout #60

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ralphc1212
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Hi Authors,

We ask to contribute our new VAE with variational nested dropout (VNDAE) presented in our recent preprint https://arxiv.org/pdf/2101.11353.pdf. It was shown to outperform VAE, BetaVAE, JointVAE and SWAE evaluated under FID and IS, on CelebA, Cifar10, Cifar100, 3D Chairs and Chest X-ray.

Please check our pull request. Thanks.

Best,
Ralph CUI
@HareshKarnan
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Hi, the input image is normalized between 0-1, did you consider using a nn.Sigmoid() activation layer instead of nn.Tanh() as the output activation of your decoder?
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@ralphc1212 @HareshKarnan