PAINET proposes an SE(3)-equivariant transformer with physics-inspired attention from energy minimization for 3D dynamics modeling, reporting 4.7-41.5% error reductions on human motion, molecular, and protein benchmarks.
Further refinements exploit local coordinate frames to process higher- order geometric features (Liu et al., 2022; Du et al., 2022; Han et al., 2024b; Cen et al.,
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PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling
PAINET proposes an SE(3)-equivariant transformer with physics-inspired attention from energy minimization for 3D dynamics modeling, reporting 4.7-41.5% error reductions on human motion, molecular, and protein benchmarks.