Bruno Sudret

According to our database, Bruno Sudret authored at least 41 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis.

Maliki Moustapha, Pietro Parisi, Stefano Marelli, Bruno Sudret

Reliab. Eng. Syst. Saf., 2024

A survey on multi-fidelity surrogates for simulators with functional outputs: unified framework and benchmark.

Lucas Brunel, Mathieu Balesdent, Loïc Brevault, Rodolphe Le Riche, Bruno Sudret

CoRR, 2024

Maximum a Posteriori Estimation for Linear Structural Dynamics Models Using Bayesian Optimization with Rational Polynomial Chaos Expansions.

Felix Schneider, Iason Papaioannou, Bruno Sudret, Gerhard Müller

CoRR, 2024

2023

Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX).

Styfen Schär, Stefano Marelli, Bruno Sudret

CoRR, 2023

2022

Sequential Active Learning of Low-Dimensional Model Representations for Reliability Analysis.

Max Ehre, Iason Papaioannou, Bruno Sudret, Daniel Straub

SIAM J. Sci. Comput., 2022

Editorial for the special issue on "sensitivity analysis of model outputs" reliability engineering and system safety.

Bertrand Iooss, Bruno Sudret, Samuele Lo Piano, Clémentine Prieur

Reliab. Eng. Syst. Saf., 2022

Learning non-stationary and discontinuous functions using clustering, classification and Gaussian process modelling.

Maliki Moustapha, Bruno Sudret

CoRR, 2022

A spectral surrogate model for stochastic simulators computed from trajectory samples.

Nora Lüthen, Stefano Marelli, Bruno Sudret

CoRR, 2022

2021

Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models.

Xujia Zhu, Bruno Sudret

Reliab. Eng. Syst. Saf., 2021

Emulation of Stochastic Simulators Using Generalized Lambda Models.

Xujia Zhu, Bruno Sudret

SIAM/ASA J. Uncertain. Quantification, 2021

Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark.

Nora Lüthen, Stefano Marelli, Bruno Sudret

SIAM/ASA J. Uncertain. Quantification, 2021

Bayesian model inversion using stochastic spectral embedding.

Paul-Remo Wagner, Stefano Marelli, Bruno Sudret

J. Comput. Phys., 2021

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

Nora Lüthen, Olivier Roustant, Fabrice Gamboa, Bertrand Iooss, Stefano Marelli, Bruno Sudret

CoRR, 2021

Rare event estimation using stochastic spectral embedding.

P.-R. Wagner, Stefano Marelli, Iason Papaioannou, Daniel Straub, Bruno Sudret

CoRR, 2021

2020

Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation.

Joseph B. Nagel, Jörg Rieckermann, Bruno Sudret

Reliab. Eng. Syst. Saf., 2020

Surrogate modeling based on resampled polynomial chaos expansions.

Zicheng Liu, Dominique Lesselier, Bruno Sudret, Joe Wiart

Reliab. Eng. Syst. Saf., 2020

A Two-Level Kriging-Based Approach with Active Learning for Solving Time-Variant Risk Optimization Problems.

Henrique Machado Kroetz, Maliki Moustapha, André Teófilo Beck, Bruno Sudret

Reliab. Eng. Syst. Saf., 2020

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

Nora Lüthen, Stefano Marelli, Bruno Sudret

CoRR, 2020

2019

Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions.

Roland Schöbi, Bruno Sudret

Reliab. Eng. Syst. Saf., 2019

Data-driven polynomial chaos expansion for machine learning regression.

Emiliano Torre, Stefano Marelli, Paul Embrechts, Bruno Sudret

J. Comput. Phys., 2019

2018

Implementation of directional simulation to estimate outcrossing rates in time-variant reliability analysis of structures.

Mohammad Reza Moarefzadeh, Bruno Sudret

Qual. Reliab. Eng. Int., 2018

Extending classical surrogate modelling to ultrahigh dimensional problems through supervised dimensionality reduction: a data-driven approach.

C. Lataniotis, Stefano Marelli, Bruno Sudret

CoRR, 2018

2017

Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion.

Onur Yuzugullu, Stefano Marelli, Esra Erten, Bruno Sudret, Irena Hajnsek

Remote. Sens., 2017

Surrogate Models for Oscillatory Systems Using Sparse Polynomial Chaos Expansions and Stochastic Time Warping.

Chu V. Mai, Bruno Sudret

SIAM/ASA J. Uncertain. Quantification, 2017

Sequential Design of Experiment for Sparse Polynomial Chaos Expansions.

Noura Fajraoui, Stefano Marelli, Bruno Sudret

SIAM/ASA J. Uncertain. Quantification, 2017

Uncertainty propagation of p-boxes using sparse polynomial chaos expansions.

Roland Schöbi, Bruno Sudret

J. Comput. Phys., 2017

Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions.

Evgeny Burnaev, Ivan Panin, Bruno Sudret

Ann. Math. Artif. Intell., 2017

2016

Global sensitivity analysis using low-rank tensor approximations.

Katerina Konakli, Bruno Sudret

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.

G. Deman, Katerina Konakli, Bruno Sudret, J. Kerrou, P. Perrochet, H. Benabderrahmane

Reliab. Eng. Syst. Saf., 2016

Spectral likelihood expansions for Bayesian inference.

Joseph B. Nagel, Bruno Sudret

J. Comput. Phys., 2016

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

Katerina Konakli, Bruno Sudret

J. Comput. Phys., 2016

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

Evgeny Burnaev, Ivan Panin, Bruno Sudret

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2016

2015

Computing derivative-based global sensitivity measures using polynomial chaos expansions.

Bruno Sudret, Chu V. Mai

Reliab. Eng. Syst. Saf., 2015

A new surrogate modeling technique combining Kriging and polynomial chaos expansions - Application to uncertainty analysis in computational dosimetry.

Pierric Kersaudy, Bruno Sudret, Nadège Varsier, Odile Picon, Joe Wiart

J. Comput. Phys., 2015

Bayesian Multilevel Model Calibration for Inverse Problems Under Uncertainty with Perfect Data.

Joseph B. Nagel, Bruno Sudret

J. Aerosp. Inf. Syst., 2015

Global sensitivity analysis of a morphology based electromagnetic scattering model.

Onur Yuzugullu, Stefano Marelli, Esra Erten, Bruno Sudret, Irena Hajnsek

Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2011

Adaptive sparse polynomial chaos expansion based on least angle regression.

Géraud Blatman, Bruno Sudret

J. Comput. Phys., 2011

2010

Efficient computation of global sensitivity indices using sparse polynomial chaos expansions.

Géraud Blatman, Bruno Sudret

Reliab. Eng. Syst. Saf., 2010

2008

Global sensitivity analysis using polynomial chaos expansions.

Bruno Sudret

Reliab. Eng. Syst. Saf., 2008

Probabilistic models for the extent of damage in degrading reinforced concrete structures.

Bruno Sudret

Reliab. Eng. Syst. Saf., 2008

2004

The PHI2 method: a way to compute time-variant reliability.

C. Andrieu-Renaud, Bruno Sudret, Maurice Lemaire

Reliab. Eng. Syst. Saf., 2004