xnn.hybrid#
Hybrid GNN + transformer interatomic potentials.
This family holds models that combine graph message passing with a transformer
(attention) update and a physics-based split of the energy. The flagship model
is BAMBOO (Gong et al. 2024), a graph
equivariant transformer whose energy is the sum of a semi-local neural-network
term, a charge-equilibrium electrostatic term, and an optional D3(CSO)
dispersion term.
BAMBOO reuses the shared transformer primitives in xnn.transformer
(the ExpNormalSmearing radial basis and
the EdgeMultiheadAttention core) and the
common InteratomicPotential contract, so it
plugs into the same training/deploy pipeline as every other xnn model.
Modules