We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
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
The noise $\epsilon_G$ is sampled from the Gaussian distribution, however, it implements with torch.rand_like() as follows
torch.rand_like()
noisy_node_feature = noisy_node_feature_mean + torch.rand_like(noisy_node_feature_mean) * noisy_node_feature_std.
noisy_node_feature = noisy_node_feature_mean + torch.rand_like(noisy_node_feature_mean) * noisy_node_feature_std
Maybe it should be torch.randn_like(noisy_node_feature_mean)?
torch.randn_like(noisy_node_feature_mean)
I'm looking forward to hearing back from you!
The text was updated successfully, but these errors were encountered:
No branches or pull requests
The noise$\epsilon_G$ is sampled from the Gaussian distribution, however, it implements with
torch.rand_like()as followsnoisy_node_feature = noisy_node_feature_mean + torch.rand_like(noisy_node_feature_mean) * noisy_node_feature_std.Maybe it should be
torch.randn_like(noisy_node_feature_mean)?I'm looking forward to hearing back from you!
The text was updated successfully, but these errors were encountered: