senya-ashukha/simple-equivariant-gnn
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
This tool helps computational chemists and material scientists predict molecular properties like HOMO energy. You input molecular structures, and it outputs predictions for their energy levels, which is crucial for understanding chemical reactivity and designing new materials. This is for researchers working with molecular graphs who need to quickly assess new compounds.
140 stars. No commits in the last 6 months.
Use this if you need a straightforward way to predict specific molecular properties, like HOMO energy, based on the 3D structure of molecules.
Not ideal if you need to perform complex simulations or predictions involving a wide range of molecular properties beyond simple energy levels, or if you prefer a system with extensive pre-built features.
Stars
140
Forks
12
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 14, 2022
Commits (30d)
0
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