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Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark

Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark

4 February 2020
Nora Lüthen
S. Marelli
Bruno Sudret
ArXivPDFHTML

Papers citing "Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark"

10 / 10 papers shown
Title
Uncertainty Quantification in Machine Learning for Engineering Design
  and Health Prognostics: A Tutorial
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
V. Nemani
Luca Biggio
Xun Huan
Zhen Hu
Olga Fink
Anh Tran
Yan Wang
Xiaoge Zhang
Chao Hu
AI4CE
33
75
0
07 May 2023
Hierarchical shrinkage Gaussian processes: applications to computer code
  emulation and dynamical system recovery
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery
T. Tang
Simon Mak
David B. Dunson
19
4
0
01 Feb 2023
Active Learning-based Domain Adaptive Localized Polynomial Chaos
  Expansion
Active Learning-based Domain Adaptive Localized Polynomial Chaos Expansion
Lukás Novák
Michael D. Shields
Václav Sadílek
M. Vořechovský
19
8
0
31 Jan 2023
Sparse Bayesian Learning for Complex-Valued Rational Approximations
Sparse Bayesian Learning for Complex-Valued Rational Approximations
Felix Schneider
I. Papaioannou
Gerhard Muller
18
4
0
06 Jun 2022
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic
  differential equations
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations
Weiheng Zhong
Hadi Meidani
DRL
27
36
0
21 Mar 2022
Probabilistic learning inference of boundary value problem with
  uncertainties based on Kullback-Leibler divergence under implicit constraints
Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints
Christian Soize
22
5
0
10 Feb 2022
Stochastic polynomial chaos expansions to emulate stochastic simulators
Stochastic polynomial chaos expansions to emulate stochastic simulators
X. Zhu
Bruno Sudret
21
17
0
07 Feb 2022
Extreme learning machines for variance-based global sensitivity analysis
Extreme learning machines for variance-based global sensitivity analysis
John E. Darges
A. Alexanderian
P. Gremaud
24
2
0
14 Jan 2022
Global sensitivity analysis using derivative-based sparse Poincaré
  chaos expansions
Global sensitivity analysis using derivative-based sparse Poincaré chaos expansions
Nora Lüthen
O. Roustant
Fabrice Gamboa
Bertrand Iooss
S. Marelli
Bruno Sudret
21
5
0
01 Jul 2021
Sequential active learning of low-dimensional model representations for
  reliability analysis
Sequential active learning of low-dimensional model representations for reliability analysis
Max Ehre
I. Papaioannou
Bruno Sudret
D. Štraub
19
10
0
08 Jun 2021
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