ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation
–Neural Information Processing Systems
Predicting low-energy molecular conformations given a molecular graph is an important but challenging task in computational drug discovery. Existing state-of-the-art approaches either resort to large scale transformer-based models that diffuse over conformer fields, or use computationally expensive methods to generate initial structures and diffuse over torsion angles.
Neural Information Processing Systems
Feb-18-2026, 13:05:34 GMT
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