generative-models
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wiseodd
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
 The generator loss diverges and does not converge Even after adding Gaussian noise to input the G_loss diverges. Please Help
In your blog post you have  Shouldn't that be  I think in your formulation `tr(Σ(Χ))` should be `tr(Σ^(-1)(Χ))` `μ(Χ)^(Τ) μ(Χ)` should be `μ(Χ)^(Τ) Σ^(-1)(Χ) μ(Χ)` `-log(det(Σ(Χ)))` should be...
https://github.com/wiseodd/generative-models/blob/c790d2c8add3d600c03ee9a301a969e10ccd7562/GAN/wasserstein_gan/wgan_tensorflow.py#L82-L83 in the code , you define the discriminator loss is : `D_loss = tf.reduce_mean(D_real) - tf.reduce_mean(D_fake) ` however the generator loss is: `G_loss = - tf.reduce_mean(D_fake) ` i think...
I can see the implementation computes KL div between q(z|x,c) and p(z)=N(0,I) but the original formulation has conditional prior p(z|c). Can you explain why you are still using zero mean...
Hey guys, I'm using the conditional-gan code for tensorflow version to generate garment drawings, the training images is RGB png file, labels are vectors like this [1,2,3,4,...,2]，I just changed the...
Hello WiseOdd, I have recognise you vanilla VAE, which seems pretty neat despite of the fact that does not work as I remember a Gassian noise sparse model would work....
change the deprecated torch.Varialbe api into torch.tensor with requires_grad ==true
