ak-muellerSPaiNN for machine learning driven excited-state dynamics
Meet SPaiNN, our open-source Python toolkit for machine learning driven excited-state dynamics! By combining equivariant neural networks (from SchNetPack) with SHARC’s surface hopping engine, SPaiNN makes non-adiabatic molecular dynamics faster and more accessible — without sacrificing quantum accuracy. Equivariant models shine in our tests on methyleneimmonium and alkene systems, outperforming invariant ones in accuracy and […]Meet SPaiNN, our open-source Python toolkit for machine learning driven excited-state dynamics! By combining equivariant neural networks (from SchNetPack) with SHARC’s surface hopping engine, SPaiNN makes non-adiabatic molecular dynamics faster and more accessible — without sacrificing quantum accuracy. Equivariant models shine in our tests on methyleneimmonium and alkene systems, outperforming invariant ones in accuracy and […]
