Applications and training sets of machine learning potentials
Recently, machine learning potentials (MLPs) have been attracting interest as an alternative to the computationally expensive density-functional theory (DFT) calculations. The data-driven approach in MLPs requires carefully curated training datasets, which define the valid domain of simulations. The...
Main Authors: | Changho Hong, Jaehoon Kim, Jaesun Kim, Jisu Jung, Suyeon Ju, Jeong Min Choi, Seungwu Han |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2023-10-01
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Series: | Science and Technology of Advanced Materials: Methods |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/27660400.2023.2269948 |
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