chrsmrrs/k-gnn
Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".
This project offers a way to analyze complex relationships within data, especially useful in fields like biology or chemistry where data is structured as networks or graphs. It takes in structured data (like protein interaction networks or chemical compounds) and outputs classifications or predictions based on these intricate connections. Researchers and scientists working with relational data, such as in drug discovery or materials science, would find this valuable.
190 stars. No commits in the last 6 months.
Use this if you need to classify or make predictions on data that is best represented as a graph, where the relationships between items are as important as the items themselves.
Not ideal if your data is primarily tabular or unstructured text, without inherent network-like connections.
Stars
190
Forks
44
Language
C++
License
—
Category
Last pushed
Mar 22, 2022
Commits (30d)
0
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