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Found 2 papers, 1 papers with code
PET-MAD, a universal interatomic potential for advanced materials modeling
Machine-learning interatomic potentials (MLIPs) have greatly extended the reach of atomic-scale simulations, offering the accuracy of first-principles calculations at a fraction of the effort.
Physics-inspired Equivariant Descriptors of Non-bonded Interactions
One essential ingredient in many machine learning (ML) based methods for atomistic modeling of materials and molecules is the use of locality.
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