SymDrift: One-Shot Generative Modeling under Symmetries
SymDrift addresses generating physical systems like molecules by making generative models aware of global symmetries, such as rotations. It introduces two methods—symmetrized drift in coordinate space and G-invariant embedding—to align the learned drift with the target distribution's symmetry. This results in state-of-the-art one-shot generation while significantly reducing computational cost.