-
Notifications
You must be signed in to change notification settings - Fork 276
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
Unsupervised Learning (MVRGL) #182
Labels
sslgraph
Self-supervised Learning on Graphs
Comments
Hi @MarkSttc , thank you for your interest and question. You can definitely train encoders in contrastive manner for other tasks. The simplest way is that you normally do the evaluation process. After the training and evaluation is finished, you can just take If you want to skip the evaluation, you can also do
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Thank you so much for the amazing work. This really help me a lot throughout my research period.
However, May I know how to train the model without using the eval method? I just want the trained model from contrastive lost only. and later will be visualized in the TSNE. Therefore, accuracy doesn't matter to me. Currently, I'm working with my own dataset for graph classification as downstream task.
Initially, I have tried using mvgrl.train() but seems like there is no learning progress and it gave me the error as well. Please find the attaches below for more clarification.
The text was updated successfully, but these errors were encountered: