首页|Reports from Chinese Academy of Sciences Describe Recent Advances in Machine Lea rning (Recent Advances In Machine Learning Interatomic Potentials for Cross-scal e Computational Simulation of Materials)
Reports from Chinese Academy of Sciences Describe Recent Advances in Machine Lea rning (Recent Advances In Machine Learning Interatomic Potentials for Cross-scal e Computational Simulation of Materials)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingout of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “In recent years, machinelearnin g interatomic potentials (ML-IPs) have attracted extensive attention in material s science, chemistry,biology, and various other fields, particularly for achiev ing higher precision and efficiency in conductinglarge-scale atomic simulations . This review, situated in the ML-IP applications in cross-scale computationalm odels of materials, offers a comprehensive overview of structure sampling, struc ture descriptors, andfitting methodologies for ML-IPs.”
ShanghaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
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