ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation

Predicting low-energy molecular conformations given a molecular graph is an important but challenging task in computational drug discovery. Our approach results in a straightforwardand scalable method that directly operates on all-atom coordinates with minimalassumptions. With the advantages of equivariance and flow matching, ET-Flowsignificantly increases the precision and physical validity of the generated con-formers, while being a lighter model and faster at inference.