DV-LAE reduces machine learning potential datasets by comparing local atomic environments with binary difference vectors, at the cost of a noticeable accuracy increase in some systems.
Taking materials dynamics to new extremes using machine learning interatomic potentials
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Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments
DV-LAE reduces machine learning potential datasets by comparing local atomic environments with binary difference vectors, at the cost of a noticeable accuracy increase in some systems.