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1502.03939
Cited By
Polynomial-Chaos-based Kriging
13 February 2015
R. Schöbi
Bruno Sudret
J. Wiart
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Papers citing
"Polynomial-Chaos-based Kriging"
33 / 33 papers shown
Conformalized Polynomial Chaos Expansion for Uncertainty-aware Surrogate Modeling
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Dimitris G. Giovanis
195
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Multi-level informed optimization via decomposed Kriging for large design problems under uncertainty
Enrico Ampellio
B. Gjorgiev
G. Sansavini
AI4CE
192
0
0
09 Oct 2025
Spline Dimensional Decomposition with Interpolation-based Optimal Knot Selection for Stochastic Dynamic Analysis
Yeonsu Kim
Junhan Lee
John T. Hwang
Bingran Wang
Dongjin Lee
186
0
0
19 May 2025
Surrogate modeling for probability distribution estimation:uniform or adaptive design?
Reliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2024
Maijia Su
Ziqi Wang
O. Bursi
M. Broccardo
206
9
0
10 Apr 2024
Computing conservative probabilities of rare events with surrogates
Nicolas Bousquet
318
0
0
26 Mar 2024
Sensitivity Analyses of a Multi-Physics Long-Term Clogging Model For Steam Generators
International Journal for Uncertainty Quantification (IJUQ), 2024
Edgar Jaber
V. Chabridon
Emmanuel Remy
Michael Baudin
Didier Lucor
Mathilde Mougeot
Bertrand Iooss
315
3
0
11 Jan 2024
Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis
Reliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2023
M. Moustapha
Pietro Parisi
S. Marelli
Bruno Sudret
170
25
0
31 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
Mechanical systems and signal processing (MSSP), 2023
V. Nemani
Luca Biggio
Xun Huan
Zhen Hu
Olga Fink
Anh Tran
Yan Wang
Xiaoge Zhang
Chao Hu
AI4CE
320
148
0
07 May 2023
Active learning for structural reliability analysis with multiple limit state functions through variance-enhanced PC-Kriging surrogate models
A. J.Moran
P. G. Morato
P. Rigo
AI4CE
159
2
0
23 Feb 2023
Multielement polynomial chaos Kriging-based metamodelling for Bayesian inference of non-smooth systems
Applied Mathematical Modelling (Appl. Math. Model.), 2022
J. C. García-Merino
C. Calvo-Jurado
E. Martínez-Paneda
E. García-Macías
157
13
0
05 Dec 2022
Recent Advances in Uncertainty Quantification Methods for Engineering Problems
Dinesh Kumar
Farid Ahmed
S. Usman
A. Alajo
S. B. Alam
336
8
0
06 Nov 2022
An adaptive multi-fidelity sampling framework for safety analysis of connected and automated vehicles
Xianliang Gong
Shuo Feng
Yulin Pan
311
9
0
25 Oct 2022
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)
Journal of Computational Physics (JCP), 2022
Paul Novello
Gaël Poëtte
D. Lugato
S. Peluchon
P. Congedo
AI4CE
523
12
0
27 Sep 2022
A connection between probability, physics and neural networks
Sascha Ranftl
PINN
232
11
0
26 Sep 2022
Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics
Journal of Computational Physics (JCP), 2022
J. Akian
L. Bonnet
H. Owhadi
Éric Savin
295
31
0
03 Jun 2022
Machine Learning in Aerodynamic Shape Optimization
Progress in Aerospace Sciences (Prog. Aerosp. Sci.), 2022
Ji-chao Li
Xiaosong Du
J. Martins
AI4CE
383
294
0
15 Feb 2022
State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning
Sourav Das
S. Tesfamariam
PINN
AI4CE
223
26
0
13 Feb 2022
PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty
Paz Fink Shustin
Shashanka Ubaru
Małgorzata J. Zimoń
Songtao Lu
Vasileios Kalantzis
L. Horesh
H. Avron
419
3
0
10 Feb 2022
Deep convolutional neural network for shape optimization using level-set approach
Wrik Mallik
N. Farvolden
J. Jelovica
R. Jaiman
178
5
0
17 Jan 2022
Recursive Estimation of a Failure Probability for a Lipschitz Function
SMAI Journal of Computational Mathematics (SMAI-JCM), 2021
Lucie Bernard
Albert Cohen
Arnaud Guyader Lpsm
Florent Malrieu
148
2
0
28 Jul 2021
Surrogate assisted active subspace and active subspace assisted surrogate -- A new paradigm for high dimensional structural reliability analysis
Computer Methods in Applied Mechanics and Engineering (CMAME), 2021
N. N.
S. Chakraborty
224
36
0
11 May 2021
Gradient-enhanced multifidelity neural networks for high-dimensional function approximation
Design Automation Conference (DAC), 2021
J. Nagawkar
Leifur Þ. Leifsson
146
0
0
23 Mar 2021
Combining Gaussian processes and polynomial chaos expansions for stochastic nonlinear model predictive control
E. Bradford
Lars Imsland
114
6
0
09 Mar 2021
Simulation free reliability analysis: A physics-informed deep learning based approach
S. Chakraborty
AI4CE
184
20
0
04 May 2020
Stochastic spectral embedding
International Journal for Uncertainty Quantification (IJUQ), 2020
S. Marelli
Paul Wagner
C. Lataniotis
Bruno Sudret
262
26
0
09 Apr 2020
Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark
Nora Lüthen
S. Marelli
Bruno Sudret
671
216
0
04 Feb 2020
Surrogate-Based Bayesian Inverse Modeling of the Hydrological System: An Adaptive Approach Considering Surrogate Approximation Error
Jiangjiang Zhang
Q. Zheng
Dingjiang Chen
Laosheng Wu
L. Zeng
302
42
0
10 Jul 2018
On efficient global optimization via universal Kriging surrogate models
P. Palar
K. Shimoyama
37
49
0
23 Mar 2018
Gradient-based Optimization for Regression in the Functional Tensor-Train Format
Alex A. Gorodetsky
J. Jakeman
332
38
0
03 Jan 2018
The Gaussian process modelling module in UQLab
C. Lataniotis
S. Marelli
Bruno Sudret
GP
211
12
0
27 Sep 2017
Hierarchical Kriging for multi-fidelity aero-servo-elastic simulators - Application to extreme loads on wind turbines
Imad Abdallah
S. Marelli
Bruno Sudret
136
31
0
22 Sep 2017
Metamodel-based sensitivity analysis: Polynomial chaos expansions and Gaussian processes
Loic Le Gratiet
S. Marelli
Bruno Sudret
204
166
0
14 Jun 2016
Sparse polynomial chaos expansions of frequency response functions using stochastic frequency transformation
V. Yaghoubi
S. Marelli
Bruno Sudret
T. Abrahamsson
210
61
0
06 Jun 2016
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