Bruno Sudret
Orcid: 0000-0002-9501-7395
According to our database1,
Bruno Sudret
authored at least 39 papers
between 2004 and 2024.
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Bibliography
2024
Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis.
Reliab. Eng. Syst. Saf., 2024
2023
Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX).
CoRR, 2023
2022
Sequential Active Learning of Low-Dimensional Model Representations for Reliability Analysis.
SIAM J. Sci. Comput., 2022
Editorial for the special issue on "sensitivity analysis of model outputs" reliability engineering and system safety.
Reliab. Eng. Syst. Saf., 2022
Learning non-stationary and discontinuous functions using clustering, classification and Gaussian process modelling.
CoRR, 2022
A spectral surrogate model for stochastic simulators computed from trajectory samples.
CoRR, 2022
2021
Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models.
Reliab. Eng. Syst. Saf., 2021
SIAM/ASA J. Uncertain. Quantification, 2021
SIAM/ASA J. Uncertain. Quantification, 2021
CoRR, 2021
2020
Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation.
Reliab. Eng. Syst. Saf., 2020
Reliab. Eng. Syst. Saf., 2020
A Two-Level Kriging-Based Approach with Active Learning for Solving Time-Variant Risk Optimization Problems.
Reliab. Eng. Syst. Saf., 2020
CoRR, 2020
2019
Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2019
J. Comput. Phys., 2019
2018
Implementation of directional simulation to estimate outcrossing rates in time-variant reliability analysis of structures.
Qual. Reliab. Eng. Int., 2018
Extending classical surrogate modelling to ultrahigh dimensional problems through supervised dimensionality reduction: a data-driven approach.
CoRR, 2018
2017
Remote. Sens., 2017
Surrogate Models for Oscillatory Systems Using Sparse Polynomial Chaos Expansions and Stochastic Time Warping.
SIAM/ASA J. Uncertain. Quantification, 2017
SIAM/ASA J. Uncertain. Quantification, 2017
J. Comput. Phys., 2017
Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions.
Ann. Math. Artif. Intell., 2017
2016
Reliab. Eng. Syst. Saf., 2016
Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model.
Reliab. Eng. Syst. Saf., 2016
Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions.
J. Comput. Phys., 2016
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2016
2015
Computing derivative-based global sensitivity measures using polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2015
A new surrogate modeling technique combining Kriging and polynomial chaos expansions - Application to uncertainty analysis in computational dosimetry.
J. Comput. Phys., 2015
Bayesian Multilevel Model Calibration for Inverse Problems Under Uncertainty with Perfect Data.
J. Aerosp. Inf. Syst., 2015
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015
2011
J. Comput. Phys., 2011
2010
Efficient computation of global sensitivity indices using sparse polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2010
2008
Reliab. Eng. Syst. Saf., 2008
Probabilistic models for the extent of damage in degrading reinforced concrete structures.
Reliab. Eng. Syst. Saf., 2008
2004
Reliab. Eng. Syst. Saf., 2004