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Small-supercell and Small-dataset Training Strategy of Machine Learning Interatomic Potentials for Point Defects
Machine learning interatomic potentials (MLIPs) can treat large-scale material systems with near first-principles accuracy and have been widely used to accelerate point-defect simulations. However, the training of MLIPs usually relies on large amounts of DFT data. This issue is particularly pronounc
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