中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Optimal design for kernel interpolation: Applications to uncertainty quantification

文献类型:期刊论文

作者Narayan, Akil1,2; Yan, Liang3,4; Zhou, Tao5
刊名JOURNAL OF COMPUTATIONAL PHYSICS
出版日期2021-04-01
卷号430页码:19
关键词Kernel interpolation Fekete points Cholesky decomposition with pivoting Hermite interpolation Uncertainty quantification
ISSN号0021-9991
DOI10.1016/j.jcp.2020.110094
英文摘要The paper is concerned with classic kernel interpolation methods, in addition to approximation methods that are augmented by gradient measurements. To apply kernel interpolation using radial basis functions (RBFs) in a stable way, we propose a type of quasi-optimal interpolation points, searching from a large set of candidate points, using a procedure similar to designing Fekete points or power function maximizing points that use pivot from a Cholesky decomposition. The proposed quasi-optimal points results in smaller condition number, and thus mitigates the instability of the interpolation procedure when the number of points becomes large. Applications to parametric uncertainty quantification are presented, and it is shown that the proposed interpolation method can outperform sparse grid methods in many interesting cases. We also demonstrate the new procedure can be applied to constructing gradient-enhanced Gaussian process emulators. (C) 2021 Elsevier Inc. All rights reserved.
资助项目NSF[DMS-1848508] ; AFOSR[FA9550-20-1-0338] ; NSF of China[11822111] ; NSF of China[11688101] ; NSF of China[11731006] ; NSF of China[11771081] ; Southeast University Zhishan Young Scholars Program ; National Key R&D Program of China[2020YFA0712000] ; Science Challenge Project[TZ2018001] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA25000404] ; Youth Innovation Promotion Association, CAS
WOS研究方向Computer Science ; Physics
语种英语
WOS记录号WOS:000624309300008
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/58357]  
专题中国科学院数学与系统科学研究院
通讯作者Yan, Liang
作者单位1.Univ Utah, Dept Math, Salt Lake City, UT 84112 USA
2.Univ Utah, Sci Comp & Imaging Inst, Salt Lake City, UT 84112 USA
3.Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
4.Nanjing Ctr Appl Math, Nanjing 211135, Peoples R China
5.Chinese Acad Sci, Inst Computat Math, Acad Math & Syst Sci, LSEC, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Narayan, Akil,Yan, Liang,Zhou, Tao. Optimal design for kernel interpolation: Applications to uncertainty quantification[J]. JOURNAL OF COMPUTATIONAL PHYSICS,2021,430:19.
APA Narayan, Akil,Yan, Liang,&Zhou, Tao.(2021).Optimal design for kernel interpolation: Applications to uncertainty quantification.JOURNAL OF COMPUTATIONAL PHYSICS,430,19.
MLA Narayan, Akil,et al."Optimal design for kernel interpolation: Applications to uncertainty quantification".JOURNAL OF COMPUTATIONAL PHYSICS 430(2021):19.

入库方式: OAI收割

来源:数学与系统科学研究院

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