ZZYSonny/PlanE

Implementation of the BasePlanE models and the experiments from the NeurIPS 2023 paper "PlanE: Representation Learning over Planar Graphs"

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Emerging

This project offers tools to help researchers and scientists efficiently analyze and understand complex planar graph structures. It takes in various datasets of planar graphs, such as chemical compounds (QM9CC) or specific structural graphs (P3R), and produces numerical representations or classifications that reveal the underlying structural properties. Researchers in fields like chemistry, materials science, or theoretical computer science would use this for graph-based modeling and analysis.

No commits in the last 6 months.

Use this if you need to generate complete and scalable representations of planar graphs to detect subtle structural differences or predict properties based on graph topology.

Not ideal if your graphs are not planar or if you require a simple, out-of-the-box solution without experimental setup or model tuning.

graph-analysis materials-science computational-chemistry structural-biology network-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 11 / 25

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Stars

13

Forks

2

Language

Python

License

GPL-3.0

Last pushed

Jan 27, 2024

Commits (30d)

0

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