arXiv:2606. 17233v1 Announce Type: new Abstract: In many engineering applications, a single high-fidelity model produces multiple quantities of interest (QoIs) under the same input parameters, e.
By Qitian Lu, Jafar Jafari-Asl, Panagiotis Spyridis, Lukas Novak
arXiv:2507.04553v2 Announce Type: replace-cross
Abstract: Reliability analysis traditionally relies on deterministic simulators, where identical inputs yield identical outputs. However, many real-wor...
By A. Pires, M. Moustapha, S. Marelli, B. Sudret
arXiv:2604. 25241v2 Announce Type: replace Abstract: Categorical structural optimization under aleatoric uncertainty is challenging because each design variable must be selected from a finite catalog of admissible instances, while each candidate design may require expensive stochastic finite-element evaluations.
By Zhangyong Liang, Jie Hou, Huanhuan Gao, Manyu Xiao
The paper introduces a learning-based surrogate approach for stochastic optimization problems where uncertainty depends on the decision, modeled via a nonparametric regression. It constructs a surrogate that embeds iteratively updated Jacobian estimates, using an adaptive random design that focuses sampling near the current iterate to achieve dimension‑independent convergence of the Jacobian estimates. The resulting learning‑based stochastic prox‑linear (L‑SPL) algorithm demonstrates nonasymptotic convergence rates and outperforms existing methods in sample efficiency and objective value in numerical experiments.
By Boyang Shen, Junyi Liu
arXiv:2607. 28903v1 Announce Type: cross Abstract: Variance-based global sensitivity analysis (GSA) plays a key role in uncertainty quantification by identifying the contributions of uncertain inputs to the variability of the model response.
By Isabel Corona Guevara, Yeping Hu
arXiv:2607. 05025v1 Announce Type: new Abstract: Vibration-based damage identification in civil infrastructure is a challenging, ill-posed inverse problem due to measurement noise, sparse sensor arrays, and environmental variability.
By Ana Fernandez Navamuel, A. Javier Omella, Diego Zamora-Sanchez, David Pardo