Bruno Sudret

Orcid: 0000-0002-9501-7395

According to our database1, Bruno Sudret authored at least 38 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

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

Emulation of Stochastic Simulators Using Generalized Lambda Models.
SIAM/ASA J. Uncertain. Quantification, 2021

Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark.
SIAM/ASA J. Uncertain. Quantification, 2021

Bayesian model inversion using stochastic spectral embedding.
J. Comput. Phys., 2021

Global sensitivity analysis using derivative-based sparse Poincaré chaos expansions.
CoRR, 2021

Rare event estimation using stochastic spectral embedding.
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

Surrogate modeling based on resampled polynomial chaos expansions.
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

Sparse Polynomial Chaos Expansions: Solvers, Basis Adaptivity and Meta-selection.
CoRR, 2020

2019
Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2019

Data-driven polynomial chaos expansion for machine learning regression.
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
Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion.
Remote. Sens., 2017

Surrogate Models for Oscillatory Systems Using Sparse Polynomial Chaos Expansions and Stochastic Time Warping.
SIAM/ASA J. Uncertain. Quantification, 2017

Sequential Design of Experiment for Sparse Polynomial Chaos Expansions.
SIAM/ASA J. Uncertain. Quantification, 2017

Uncertainty propagation of p-boxes using sparse polynomial chaos expansions.
J. Comput. Phys., 2017

Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions.
Ann. Math. Artif. Intell., 2017

2016
Global sensitivity analysis using low-rank tensor approximations.
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

Spectral likelihood expansions for Bayesian inference.
J. Comput. Phys., 2016

Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions.
J. Comput. Phys., 2016

Effective Design for Sobol Indices Estimation Based on Polynomial Chaos Expansions.
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

Global sensitivity analysis of a morphology based electromagnetic scattering model.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2011
Adaptive sparse polynomial chaos expansion based on least angle regression.
J. Comput. Phys., 2011

2010
Efficient computation of global sensitivity indices using sparse polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2010

2008
Global sensitivity analysis using polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2008

Probabilistic models for the extent of damage in degrading reinforced concrete structures.
Reliab. Eng. Syst. Saf., 2008

2004
The PHI2 method: a way to compute time-variant reliability.
Reliab. Eng. Syst. Saf., 2004


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