Local Density Approximation for Excited States
Physical Review XThe ground state of an homogeneous electron gas is a paradigmatic state that has been used to model and predict the electronic structure of matter at equilibrium for nearly a century.
Tim Gould, Stefano Pittalis
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Classical Density Functional Theory: The Local Density Approximation [PDF]
, 2023 We prove that the lowest free energy of a classical interacting system at temperature $T$ with a prescribed density profile $ρ(x)$ can be approximated by the local free energy $\int f_T(ρ(x))dx$, provided that $ρ$ varies slowly over sufficiently large ...
Lewin, Mathieu +2 more
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An Improved Density Peak Clustering Algorithm for Multi-Density Data
Sensors, 2022 Density peak clustering is the latest classic density-based clustering algorithm, which can directly find the cluster center without iteration. The algorithm needs to determine a unique parameter, so the selection of parameters is particularly important.
Lifeng Yin +3 more
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Optimized Density Peak Clustering Algorithm by Adaptive Aggregation Strategy
Jisuanji kexue yu tansuo, 2020 Aiming at the problem that the density peak clustering algorithm is greatly influenced by human interven-tion and parameter is sensitive, that is the improper selection of its parameter cutoff distance dc will lead to the wrong selection of initial ...
QIAN Xuezhong, JIN Hui
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Resampling algorithm for imbalanced data based on their neighbor relationship
工程科学学报, 2021 The classification of imbalanced data has become a crucial and significant research issue in many data-intensive applications. The minority samples in such applications usually contain important information.
Rui-feng LI +3 more
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Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization [PDF]
, 2004 This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability.
Harris, C. J. +3 more
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Research of Density Peaks Clustering Algorithm Based on Second-Order k Neighbors
Jisuanji kexue yu tansuo, 2021 Clustering by fast search and find of density peaks (DPC) is a new density clustering algorithm proposed in recent years. The core of the algorithm is based on local density and relative distance.
WANG Dagang, DING Shifei, ZHONG Jin
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Density Matrix Embedding Using Multiconfiguration Pair-Density Functional Theory [PDF]
, 2023 We present a quantum embedding method for ground and excited states of extended systems that uses multiconfiguration pair-density functional theory (MC-PDFT) with densities provided by periodic density matrix embedding theory (pDMET).
Matthew , Hermes +5 more
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Density Peaks Clustering Combining Relative Local Density and Nearest Neighbor Relationship [PDF]
Jisuanji kexue yu tansuo, 2023 When the density peaks algorithm deals with datasets with different densities, the wrong center points may be selected, and the problem of associated errors may occur in the sample allocation process.
WANG Weina, ZHU Yu, REN Yan
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Density-Distance Outlier Detection Algorithm Based on Natural Neighborhood
Axioms, 2023 Outlier detection is of great significance in the domain of data mining. Its task is to find those target points that are not identical to most of the object generation mechanisms.
Jiaxuan Zhang, Youlong Yang
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