首页|University of Science and Technology of China Reports Findings in Machine Learni ng (Machine Learning K-Means Clustering in Interpolative Separable Density Fitti ng Algorithm: Advancing Accurate and Efficient Cubic-Scaling Density Functional ...)
University of Science and Technology of China Reports Findings in Machine Learni ng (Machine Learning K-Means Clustering in Interpolative Separable Density Fitti ng Algorithm: Advancing Accurate and Efficient Cubic-Scaling Density Functional ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting out of Anhui, People’s Republic of China , by NewsRx editors, research stated, “Density functional perturbation theory (D FPT) is a crucial tool for accurately describing lattice dynamics. The adaptivel y compressed polarizability (ACP) method reduces the computational complexity of DFPT calculations from O() to O() by combining the interpolative separable dens ity fitting (ISDF) algorithm.”
AnhuiPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine Learning
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