danielegrattarola/SRC
Code for "Understanding Pooling in Graph Neural Networks" (TNNLS 2022).
This is a developer tool designed to help machine learning engineers and researchers working with Graph Neural Networks (GNNs). It provides a flexible framework for implementing and experimenting with different graph pooling strategies. By using this, you can define how your GNN models aggregate information from nodes into 'supernodes,' allowing you to explore various ways to simplify complex graph structures.
No commits in the last 6 months.
Use this if you are developing or researching Graph Neural Networks and need a standardized way to implement and test various graph pooling layers within your Keras models.
Not ideal if you are an end-user looking for a pre-built application to analyze graph data without diving into GNN model development.
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Language
Python
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Last pushed
Jun 02, 2022
Commits (30d)
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