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Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling - npj Computational Materials
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Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained.
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