A co-trained multifidelity mixture-of-experts MLIP partitions simulations into high- and low-capacity regions, maintains exact energy conservation and bulk modulus alignment, and runs more than twice as fast as a single high-fidelity model on a Pt+CO system.
Adaptive-precision potentials for large-scale atomistic simulations.The Journal of Chemical Physics, 162(11)
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Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations
A co-trained multifidelity mixture-of-experts MLIP partitions simulations into high- and low-capacity regions, maintains exact energy conservation and bulk modulus alignment, and runs more than twice as fast as a single high-fidelity model on a Pt+CO system.