9 papers
Gradient-enhanced global sensitivity analysis with Poincar{é} chaos expansions
O Roustant, N Lüthen, David Heredia +1
Spectral methods, also known as chaos expansions, are widely used in global sensitivity analysis (GSA), as they leverage orthogonal bases of L2 spaces to efficiently compute Sobol'…
Probabilistic function-on-function nonlinear autoregressive model for emulation and reliability analysis of stochastic dynamical systems
Zhouzhou Song, Marcos A. Valdebenito, Styfen Schär +3
Constructing accurate and computationally efficient surrogate models (or emulators) for predicting dynamical system responses is critical in many engineering domains, yet remains c…
Reliability analysis for non-deterministic limit-states using stochastic emulators
Anderson V. Pires, Maliki Moustapha, Stefano Marelli +1
Reliability analysis is a sub-field of uncertainty quantification that assesses the probability of a system performing as intended under various uncertainties. Traditionally, this…
MF-GLaM: A multifidelity stochastic emulator using generalized lambda models
K. Giannoukou, X. Zhu, S. Marelli +1
Stochastic simulators exhibit intrinsic stochasticity due to unobservable, uncontrollable, or unmodeled input variables, resulting in random outputs even at fixed input conditions.…
mNARX+: A surrogate model for complex dynamical systems using manifold-NARX and automatic feature selection
S. Schär, S. Marelli, B. Sudret
We propose an automatic approach for manifold nonlinear autoregressive with exogenous inputs (mNARX) modeling that leverages the feature-based structure of functional-NARX (F-NARX)…
Conformal prediction for full and sparse polynomial chaos expansions
A. Hatstatt, X. Zhu, B. Sudret
Polynomial Chaos Expansions (PCEs) are widely recognized for their efficient computational performance in surrogate modeling. Yet, a robust framework to quantify local model errors…