Fig. 1: Results overview.
From: A Euclidean transformer for fast and stable machine learned force fields
a Illustration of an invariant convolution. b Illustration of an SO(3) convolution. c Illustration of the Euclidean attention mechanism that underlies the SO3krates transformer. We decompose the representation of molecular structure into high dimensional invariant features and equivariant Euclidean variables (EV), which interact via self-attention. d The combination of simulation stability and computational efficiency of SO3krates enables the analysis of a broad set of properties (power spectra, folding dynamics, minima analysis, radius of gyration) on different simulation timescales.
