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A survey of unsupervised learning methods for high-dimensional
  uncertainty quantification in black-box-type problems
v1v2 (latest)

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

9 February 2022
Katiana Kontolati
Dimitrios Loukrezis
D. D. Giovanis
Lohit Vandanapu
Michael D. Shields
ArXiv (abs)PDFHTML

Papers citing "A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems"

15 / 15 papers shown
Title
High-dimensional multimodal uncertainty estimation by manifold alignment:Application to 3D right ventricular strain computations
High-dimensional multimodal uncertainty estimation by manifold alignment:Application to 3D right ventricular strain computations
Maxime Di Folco
Gabriel Bernardino
Patrick Clarysse
Nicolas Duchateau
96
1
0
21 Jan 2025
Learning signals defined on graphs with optimal transport and Gaussian process regression
Learning signals defined on graphs with optimal transport and Gaussian process regression
Raphael Carpintero Perez
Sébastien da Veiga
Josselin Garnier
B. Staber
210
1
0
21 Oct 2024
Stratospheric aerosol source inversion: Noise, variability, and
  uncertainty quantification
Stratospheric aerosol source inversion: Noise, variability, and uncertainty quantification
J. Hart
I. Manickam
M. Gulian
L. Swiler
D. Bull
T. Ehrmann
H. Brown
B. Wagman
J. Watkins
62
6
0
10 Sep 2024
NeurAM: nonlinear dimensionality reduction for uncertainty
  quantification through neural active manifolds
NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds
Andrea Zanoni
Gianluca Geraci
Matteo Salvador
Alison L. Marsden
Daniele E. Schiavazzi
41
3
0
07 Aug 2024
End-to-end Conditional Robust Optimization
End-to-end Conditional Robust Optimization
A. Chenreddy
Erick Delage
115
11
0
07 Mar 2024
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 quantification
Jungho Kim
Sang-ri Yi
Ziqi Wang
78
6
0
07 Feb 2024
Polynomial Chaos Expansions on Principal Geodesic Grassmannian
  Submanifolds for Surrogate Modeling and Uncertainty Quantification
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification
Dimitris G. Giovanis
Dimitrios Loukrezis
Ioannis G. Kevrekidis
Michael D. Shields
77
4
0
30 Jan 2024
Model-Agnostic Interpretation Framework in Machine Learning: A
  Comparative Study in NBA Sports
Model-Agnostic Interpretation Framework in Machine Learning: A Comparative Study in NBA Sports
Shun Liu
68
0
0
05 Jan 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 simulation
Jianhua Xian
Ziqi Wang
AI4CE
65
11
0
30 Sep 2023
Learning in latent spaces improves the predictive accuracy of deep
  neural operators
Learning in latent spaces improves the predictive accuracy of deep neural operators
Katiana Kontolati
S. Goswami
George Karniadakis
Michael D. Shields
AI4CE
88
22
0
15 Apr 2023
Probabilistic partition of unity networks for high-dimensional
  regression problems
Probabilistic partition of unity networks for high-dimensional regression problems
Tiffany Fan
N. Trask
M. DÉlia
Eric F. Darve
60
1
0
06 Oct 2022
Solving Coupled Differential Equation Groups Using PINO-CDE
Solving Coupled Differential Equation Groups Using PINO-CDE
Wenhao Ding
Qing He
Hanghang Tong
Qingjing Wang
Ping Wang
OODAI4CE
52
4
0
01 Oct 2022
On the influence of over-parameterization in manifold based surrogates
  and deep neural operators
On the influence of over-parameterization in manifold based surrogates and deep neural operators
Katiana Kontolati
S. Goswami
Michael D. Shields
George Karniadakis
73
42
0
09 Mar 2022
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
49
9
0
28 Sep 2021
Active Learning with Multifidelity Modeling for Efficient Rare Event
  Simulation
Active Learning with Multifidelity Modeling for Efficient Rare Event Simulation
Somayajulu L. N. Dhulipala
Michael D. Shields
B. Spencer
C. Bolisetti
A. Slaughter
V. Labouré
P. Chakroborty
56
24
0
25 Jun 2021
1