Matthias G. R. Faes

23 papers Journal 21Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Active learning Kriging with functional dimension reduction for reliability analysis of stochastic dynamical systems.
Reliab. Eng. Syst. Saf.
Zhouzhou Song, Chao Dang, Marcos A. Valdebenito, Matthias G. R. Faes
2026 J jnl
Sensitivity estimation of stochastic output with respect to distribution parameters of stochastic inputs.
Reliab. Eng. Syst. Saf.
Xuan-Yi Zhang, Yan-Gang Zhao, Marcos A. Valdebenito, Matthias G. R. Faes
2026 J jnl
Variance-reduced estimation of Third-order statistics using control variates with splitting.
Reliab. Eng. Syst. Saf.
Cristóbal H. Acevedo, Marcos A. Valdebenito, Iván V. González, Hector A. Jensen, Matthias G. R. Faes
2025 J jnl
A Bayesian piecewise fitting method for estimating probability distributions of performance functions.
Reliab. Eng. Syst. Saf.
Yan-Gang Zhao, Ya-Ting Liu, Pei-Pei Li, Ye-Yao Weng, Marcos A. Valdebenito, Matthias G. R. Faes
2025 J jnl
Asymptotic subset simulation: An efficient extrapolation tool for small probabilities approximation.
Reliab. Eng. Syst. Saf.
Mohsen Rashki, Matthias G. R. Faes, Pengfei Wei, Jingwen Song
2025 J jnl
Efficient forward and inverse uncertainty quantification for dynamical systems based on dimension reduction and Kriging surrogate modeling in functional space.
CoRR
Zhouzhou Song, Weiyun Xu, Marcos A. Valdebenito, Matthias G. R. Faes
2025 J jnl
On fractional moment estimation from polynomial chaos expansion.
Reliab. Eng. Syst. Saf.
Lukás Novák, Marcos A. Valdebenito, Matthias G. R. Faes
2025 J jnl
On the impact of geometric variance on the performance of formed parts: A probabilistic approach on the example of airbag pressure bins.
CoRR
Lukas Schnelle, Niklas Fehlemann, Ali O. M. Kilicsoy, Niklas Bechler, Marcos A. Valdebenito, Yannis P. Korkolis, Matthias G. R. Faes, Sebastian Münstermann, Kai-Uwe Schröder
2024 J jnl
Line sampling for time-variant failure probability estimation using an adaptive combination approach.
Reliab. Eng. Syst. Saf.
Xiukai Yuan, Weiming Zheng, Chaofan Zhao, Marcos A. Valdebenito, Matthias G. R. Faes, Yiwei Dong
2024 J jnl
On Fractional Moment Estimation from Polynomial Chaos Expansion.
CoRR
Lukás Novák, Marcos A. Valdebenito, Matthias G. R. Faes
2024 J jnl
Sobolev Neural Network With Residual Weighting as a Surrogate in Linear and Non-Linear Mechanics.
IEEE Access
Ali O. M. Kilicsoy, Jan Liedmann, Marcos A. Valdebenito, F.-J. Barthold, Matthias G. R. Faes
2024 J jnl
Sobolev neural network with residual weighting as a surrogate in linear and non-linear mechanics.
CoRR
Ali O. M. Kilicsoy, Jan Liedmann, Marcos A. Valdebenito, F.-J. Barthold, Matthias G. R. Faes
2023 J jnl
Global failure probability function estimation based on an adaptive strategy and combination algorithm.
Reliab. Eng. Syst. Saf.
Xiukai Yuan, Yugeng Qian, Jingqiang Chen, Matthias G. R. Faes, Marcos A. Valdebenito, Michael Beer
2022 J jnl
Parallel adaptive Bayesian quadrature for rare event estimation.
Reliab. Eng. Syst. Saf.
Chao Dang, Pengfei Wei, Matthias G. R. Faes, Marcos A. Valdebenito, Michael Beer
2021 J jnl
Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics.
Adv. Eng. Softw.
Matthias G. R. Faes, Marcos A. Valdebenito, Xiukai Yuan, Pengfei Wei, Michael Beer
2021 J jnl
Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA.
IEEE Trans. Biomed. Eng.
Laura Bartsoen, Matthias G. R. Faes, Mariska Wesseling, Roel Wirix-Speetjens, David Moens, Ilse Jonkers, Jos Vander Sloten
2021 J jnl
Decoupled reliability-based optimization using Markov chain Monte Carlo in augmented space.
Adv. Eng. Softw.
Xiukai Yuan, Shaolong Liu, Marcos A. Valdebenito, Matthias G. R. Faes, Danko J. Jerez, Hector A. Jensen, Michael Beer
2021 J jnl
Efficient imprecise reliability analysis using the Augmented Space Integral.
Reliab. Eng. Syst. Saf.
Xiukai Yuan, Matthias G. R. Faes, Shaolong Liu, Marcos A. Valdebenito, Michael Beer
2021 J jnl
On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation.
Int. J. Intell. Syst.
Lechang Yang, Pidong Wang, Wenhua Zhao, Chenxing Wang, Xiuli Wu, Matthias G. R. Faes
2019 — conf
A fast inverse approach for the quantification of set-theoretical uncertainty.
SSCI
Lars Bogaerts, Matthias G. R. Faes, David Moens
2019 J jnl
Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts.
Comput. Math. Appl.
Matthias G. R. Faes, Ghosh Dastidar Sabyasachi, David Moens
2017 — conf
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure.
SSCI
Matteo Broggi, Matthias G. R. Faes, Edoardo Patelli, Yves Govers, David Moens, Michael Beer
2016 J jnl
Process Monitoring of Extrusion Based 3D Printing via Laser Scanning.
CoRR
Matthias G. R. Faes, Wim Abbeloos, Frederik Vogeler, Hans Valkenaers, Kurt Coppens, Toon Goedemé, Eleonora Ferraris