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Grassmannian diffusion maps based dimension reduction and classification
  for high-dimensional data
v1v2v3 (latest)

Grassmannian diffusion maps based dimension reduction and classification for high-dimensional data

16 September 2020
K. D. Santos
D. D. Giovanis
Michael D. Shields
    DiffM
ArXiv (abs)PDFHTML

Papers citing "Grassmannian diffusion maps based dimension reduction and classification for high-dimensional data"

7 / 7 papers shown
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantificationReliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2024
Jungho Kim
Sang-ri Yi
Ziqi Wang
299
15
0
07 Feb 2024
A physics and data co-driven surrogate modeling method for
  high-dimensional rare event simulation
A physics and data co-driven surrogate modeling method for high-dimensional rare event simulationJournal of Computational Physics (JCP), 2023
Jianhua Xian
Ziqi Wang
AI4CE
299
14
0
30 Sep 2023
AI-enhanced iterative solvers for accelerating the solution of large
  scale parametrized systems
AI-enhanced iterative solvers for accelerating the solution of large scale parametrized systemsInternational Journal for Numerical Methods in Engineering (IJNME), 2022
Stefanos Nikolopoulos
I. Kalogeris
V. Papadopoulos
G. Stavroulakis
624
16
0
06 Jul 2022
CCP: Correlated Clustering and Projection for Dimensionality Reduction
CCP: Correlated Clustering and Projection for Dimensionality Reduction
Yuta Hozumi
Rui Wang
G. Wei
135
15
0
08 Jun 2022
A survey of unsupervised learning methods for high-dimensional
  uncertainty quantification in black-box-type problems
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problemsJournal of Computational Physics (JCP), 2022
Katiana Kontolati
Dimitrios Loukrezis
D. D. Giovanis
Lohit Vandanapu
Michael D. Shields
349
58
0
09 Feb 2022
Data-driven Uncertainty Quantification in Computational Human Head
  Models
Data-driven Uncertainty Quantification in Computational Human Head ModelsComputer Methods in Applied Mechanics and Engineering (CMAME), 2021
K. Upadhyay
Dimitris G. Giovanis
A. Alshareef
A. Knutsen
Curtis L. Johnson
A. Carass
P. Bayly
Michael D. Shields
K. Ramesh
AI4CE
251
14
0
29 Oct 2021
Grassmannian diffusion maps based surrogate modeling via geometric
  harmonics
Grassmannian diffusion maps based surrogate modeling via geometric harmonics
K. R. D. dos Santos
Dimitris G. Giovanis
Katiana Kontolati
Dimitrios Loukrezis
Michael D. Shields
188
11
0
28 Sep 2021
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