ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1606.04273
  4. Cited By
Metamodel-based sensitivity analysis: Polynomial chaos expansions and
  Gaussian processes

Metamodel-based sensitivity analysis: Polynomial chaos expansions and Gaussian processes

14 June 2016
Loic Le Gratiet
S. Marelli
Bruno Sudret
ArXivPDFHTML

Papers citing "Metamodel-based sensitivity analysis: Polynomial chaos expansions and Gaussian processes"

11 / 11 papers shown
Title
Surrogate-based global sensitivity analysis with statistical guarantees
  via floodgate
Surrogate-based global sensitivity analysis with statistical guarantees via floodgate
Massimo Aufiero
Lucas Janson
AI4CE
17
3
0
11 Aug 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and
  Vibroacoustic
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic
Barbara Z Cunha
C. Droz
A. Zine
Stéphane Foulard
M. Ichchou
AI4CE
35
84
0
13 Apr 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
Uncertainty quantification of a three-dimensional in-stent restenosis
  model with surrogate modelling
Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling
Dongwei Ye
Pavel S. Zun
Valeria Krzhizhanovskaya
Alfons G. Hoekstra
24
1
0
11 Nov 2021
Graph Neural Network Guided Local Search for the Traveling Salesperson
  Problem
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
Benjamin H. Hudson
Qingbiao Li
Matthew Malencia
Amanda Prorok
27
63
0
11 Oct 2021
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
26
5
0
01 Jul 2021
Derivative-based global sensitivity analysis for models with
  high-dimensional inputs and functional outputs
Derivative-based global sensitivity analysis for models with high-dimensional inputs and functional outputs
Helen L. Cleaves
A. Alexanderian
H. Guy
Ralph C. Smith
Meilin Yu
17
10
0
12 Feb 2019
Principal component analysis and sparse polynomial chaos expansions for
  global sensitivity analysis and model calibration: application to urban
  drainage simulation
Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: application to urban drainage simulation
J. Nagel
J. Rieckermann
Bruno Sudret
6
63
0
11 Sep 2017
Shapley effects for sensitivity analysis with correlated inputs:
  comparisons with Sobol' indices, numerical estimation and applications
Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications
Bertrand Iooss
Clémentine Prieur
FAtt
28
96
0
05 Jul 2017
Global sensitivity analysis in the context of imprecise probabilities
  (p-boxes) using sparse polynomial chaos expansions
Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions
R. Schöbi
Bruno Sudret
21
60
0
29 May 2017
Global sensitivity analysis using low-rank tensor approximations
Global sensitivity analysis using low-rank tensor approximations
K. Konakli
Bruno Sudret
23
77
0
29 May 2016
1