atomicarchitects/equiformer
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
This project helps scientists and researchers in chemistry and materials science to predict the properties of 3D molecular structures. By inputting the atomic arrangement of a molecule, it outputs predictions for various chemical properties and energy states. This is especially useful for computational chemists, materials scientists, and drug discovery researchers.
274 stars. No commits in the last 6 months.
Use this if you need to accurately model the energies and forces within 3D atomic systems to understand their behavior or predict material properties.
Not ideal if you are working with non-atomic graph data or do not require predictions that respect the 3D geometry of molecules.
Stars
274
Forks
52
Language
Python
License
MIT
Category
Last pushed
Feb 11, 2025
Commits (30d)
0
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