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
I am thinking to use Graph2vec for learning graph similarity learning.
Given two graphs, I am thinking to get embeddings of the two graphs and then take the cosine similarity of the two graphs.
May graphs would have around 5000 nodes and 4000 edges.
Is Graph2vec a good fit for this task?
The text was updated successfully, but these errors were encountered:
Dear @smith-co,
Could you star the repo first?
Yes it is! I would recommend using the Karateclub implementation!
https://github.com/benedekrozemberczki/karateclub
Bests,
Benedek
Sorry, something went wrong.
@benedekrozemberczki of course - added star to the repo :-)
I am looking into the Karateclub repo. Can you please point me how to create the API to create graphs for Karateclub?
@benedekrozemberczki do you have an example where you build a graph from scratch i.e. create nodes and then add edges?
No branches or pull requests
I am thinking to use Graph2vec for learning graph similarity learning.
Given two graphs, I am thinking to get embeddings of the two graphs and then take the cosine similarity of the two graphs.
May graphs would have around 5000 nodes and 4000 edges.
Is Graph2vec a good fit for this task?
The text was updated successfully, but these errors were encountered: