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Surrogate models for oscillatory systems using sparse polynomial chaos
  expansions and stochastic time warping
v1v2 (latest)

Surrogate models for oscillatory systems using sparse polynomial chaos expansions and stochastic time warping

29 September 2016
Chu V. Mai
Bruno Sudret
ArXiv (abs)PDFHTML

Papers citing "Surrogate models for oscillatory systems using sparse polynomial chaos expansions and stochastic time warping"

5 / 5 papers shown
Bayesian full waveform inversion with sequential surrogate model refinement
Bayesian full waveform inversion with sequential surrogate model refinementGeophysical Journal International (GJI), 2025
G. Meles
S. Marelli
N. Linde
266
1
0
06 May 2025
Emulating the dynamics of complex systems using autoregressive models on
  manifolds (mNARX)
Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX)Mechanical systems and signal processing (MSSP), 2023
Styfen Schär
S. Marelli
Bruno Sudret
AI4CE
320
25
0
28 Jun 2023
A two-level Kriging-based approach with active learning for solving
  time-variant risk optimization problems
A two-level Kriging-based approach with active learning for solving time-variant risk optimization problemsReliability Engineering & System Safety (RESS), 2020
H. M. Kroetz
M. Moustapha
A. Beck
Bruno Sudret
AI4CE
118
48
0
08 Jul 2020
Variance-based sensitivity analysis for time-dependent processes
Variance-based sensitivity analysis for time-dependent processes
A. Alexanderian
P. Gremaud
Ralph C. Smith
179
60
0
21 Nov 2017
Sparse polynomial chaos expansions of frequency response functions using
  stochastic frequency transformation
Sparse polynomial chaos expansions of frequency response functions using stochastic frequency transformation
V. Yaghoubi
S. Marelli
Bruno Sudret
T. Abrahamsson
211
61
0
06 Jun 2016
1
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