Add survey on GNNs from a graph structural information perspective #78
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Added "A Network Science perspective of Graph Convolutional Networks: A survey" https://arxiv.org/abs/2301.04824 to survey papers
Add survey on GNNs
|
Update |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
I've recently shared our new survey on arxiv: A Network Science perspective of Graph Convolutional Networks: A survey
We survey GNNs from a graph structural information perspective and propose a novel taxonomy that classifies GCNs from three structural information angles, i.e., the layer-wise message aggregation scope, the message content, and the overall learning scope. Thus, adding this paper will make the list more comprehensive and spread awareness of the connections between traditional network science and GNNs.
Thank you for your consideration.