frcnt/equivariant-neural-diffusion
[NeurIPS 2024] Equivariant Neural Diffusion for Molecule Generation
This project helps chemists and materials scientists generate new molecular structures with specific properties. It takes information about desired atomic positions and features as input and outputs novel molecule designs, accelerating drug discovery or material design workflows. The end user is a researcher or scientist working in chemistry, pharmaceuticals, or materials science who needs to explore new molecular compositions.
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Use this if you need to computationally design or discover new molecules based on desired atomic arrangements and features, for applications like drug development or material synthesis.
Not ideal if you are looking to analyze existing molecular structures or simulate their interactions rather than generate new ones.
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Language
Python
License
MIT
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Last pushed
Apr 21, 2025
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