-
Notifications
You must be signed in to change notification settings - Fork 622
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Code for Minibatch Discrimination on MNIST Missing #4
Comments
+1 |
👍 We're trying to compare to your results, and it'd be really helpful to be able to be sure we didn't get something stupid wrong in plugging together |
@wenyangfu @xunhuang1995: I talked to the authors about this offline, and they told me that the just used the same model as for CIFAR/SVHN for MNIST minibatch. My fork has a |
Hi @dougalsutherland, just wondering does it mean minibatch can only work with conv discriminative model instead of dense layer one? |
@AilsaF I don't know if it wouldn't work with dense layers, just that they used the convolutional one. You could try it. :) |
Hi, I've been trying to reproduce a minibatch discrimination GAN for MNIST based on the paper, but I keep getting poor results. Would it be possible for "train_mnist_minibatch_discrimination.py" to be uploaded to the repo? I assume it exists, since MNIST digits generated via minibatch discrimination were shown in the paper. Thanks for your time!
The text was updated successfully, but these errors were encountered: