Response surfaces and sensitivity analyses for an environmental model of dose calculations. - Bertrand Iooss; François Van Dorpe; Nicolas Devictor (Reliab. Eng. Syst. Saf., 2006)

An efficient methodology for modeling complex computer codes with Gaussian processes. - Amandine Marrel; Bertrand Iooss; François Van Dorpe; Elena Volkova (Comput. Stat. Data Anal., 2008)

Contributions au traitement des incertitudes en modélisation numérique : propagation d'ondes en milieu aléatoire et analyse statistique d'expériences simulées. (Contributions to the uncertainty management in numerical modelisation: wave propagation in random media and analysis of computer experiments). - Bertrand Iooss (2009)

Global sensitivity analysis of computer models with functional inputs. - Bertrand Iooss; Mathieu Ribatet (Reliab. Eng. Syst. Saf., 2009)

Calculations of Sobol indices for the Gaussian process metamodel. - Amandine Marrel; Bertrand Iooss; Béatrice Laurent; Olivier Roustant (Reliab. Eng. Syst. Saf., 2009)

Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations. - Benjamin Auder; Agnès De Crecy; Bertrand Iooss; Michel Marquès (Reliab. Eng. Syst. Saf., 2012)

Global sensitivity analysis of stochastic computer models with joint metamodels. - Amandine Marrel; Bertrand Iooss; Sébastien Da Veiga; Mathieu Ribatet (Stat. Comput., 2012)

Numerical studies of space-filling designs: optimization of Latin Hypercube Samples and subprojection properties. - G. Damblin; Mathieu Couplet; Bertrand Iooss (J. Simulation, 2013)

Derivative-based global sensitivity measures: General links with Sobol' indices and numerical tests. - Matieyendou Lamboni; Bertrand Iooss; A.-L. Popelin; Fabrice Gamboa (Math. Comput. Simul., 2013)

Visualizing statistical analysis of curve datasets in ParaView. - Alejandro Ribés; Joachim Pouderoux; Anne-Laure Popelin; Bertrand Iooss (IEEE VAST, 2014)

A Bayesian Approach for Global Sensitivity Analysis of (Multifidelity) Computer Codes. - Loïc Le Gratiet; Claire Cannamela; Bertrand Iooss (SIAM/ASA J. Uncertain. Quantification, 2014)

Crossed-derivative based sensitivity measures for interaction screening. - Olivier Roustant; Jana Fruth; Bertrand Iooss; Sonja Kuhnt (Math. Comput. Simul., 2014)

Application of the control variate technique to estimation of total sensitivity indices. - Sergei S. Kucherenko; B. Delpuech; Bertrand Iooss; Stefano Tarantola (Reliab. Eng. Syst. Saf., 2015)

Stochastic Simulators Based Optimization by Gaussian Process Metamodels - Application to Maintenance Investments Planning Issues. - Thomas Browne; Bertrand Iooss; Loïc Le Gratiet; Jérôme Lonchampt; Emmanuel Remy (Qual. Reliab. Eng. Int., 2016)

Melissa: large scale in transit sensitivity analysis avoiding intermediate files. - Théophile Terraz; Alejandro Ribés; Yvan Fournier; Bertrand Iooss; Bruno Raffin (SC, 2017)

Canonical Moments for Optimal Uncertainty Quantification on a Variety. - Jérôme Stenger; Fabrice Gamboa; Merlin Keller; Bertrand Iooss (GSI, 2019)

Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation. - Sibo Cheng; Jean-Philippe Argaud; Bertrand Iooss; Didier Lucor; Angélique Ponçot (CoRR, 2019)

Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes. - Bertrand Iooss; Loïc Le Gratiet (Reliab. Eng. Syst. Saf., 2019)

Statistical Identification of Penalizing Configurations in High-dimensional Thermal-hydraulic Numerical Experiments: The ICSCREAM Methodology. - Amandine Marrel; Bertrand Iooss; Vincent Chabridon (CoRR, 2020)

Model Predictivity Assessment: Incremental Test-Set Selection and Accuracy Evaluation. - Elias Fekhari; Bertrand Iooss; Joseph Muré; Luc Pronzato; Maria-João Rendas (SIS, 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)

Developments and applications of Shapley effects to reliability-oriented sensitivity analysis with correlated inputs. - Marouane Il Idrissi; Vincent Chabridon; Bertrand Iooss (Environ. Model. Softw., 2021)

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support. - Saman Razavi; Anthony J. Jakeman; Andrea Saltelli; Clémentine Prieur; Bertrand Iooss; Emanuele Borgonovo; Elmar Plischke; Samuele Lo Piano; Takuya Iwanaga; William E. Becker; Stefano Tarantola; Joseph H. A. Guillaume; et al. (Environ. Model. Softw., 2021)

Model selection based on validation criteria for Gaussian process regression: An application with highlights on the predictive variance. - Charles Demay; Bertrand Iooss; Loïc Le Gratiet; Amandine Marrel (Qual. Reliab. Eng. Int., 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)

An Information Geometry Approach to Robustness Analysis for the Uncertainty Quantification of Computer Codes. - Clement Gauchy; Jérôme Stenger; Roman Sueur; Bertrand Iooss (Technometrics, 2022)

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review. - Sibo Cheng; César Quilodrán Casas; Said Ouala; Alban Farchi; Che Liu; Pierre Tandeo; Ronan Fablet; Didier Lucor; Bertrand Iooss; Julien Brajard; Dunhui Xiao; Tijana Janjic; et al. (IEEE CAA J. Autom. Sinica, 2023)

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees. - Edgar Jaber; Vincent Blot; Nicolas J.-B. Brunel; Vincent Chabridon; Emmanuel Remy; Bertrand Iooss; Didier Lucor; Mathilde Mougeot; Alessandro Leite (CoRR, 2024)

Proportional Marginal Effects for Global Sensitivity Analysis. - Margot Herin; Marouane Il Idrissi; Vincent Chabridon; Bertrand Iooss (SIAM/ASA J. Uncertain. Quantification, 2024)

Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation. - Amandine Marrel; Bertrand Iooss (Reliab. Eng. Syst. Saf., 2024)

Probabilistic surrogate modeling by Gaussian process: A new estimation algorithm for more robust prediction. - Amandine Marrel; Bertrand Iooss (Reliab. Eng. Syst. Saf., 2024)

Hoeffding decomposition of functions of random dependent variables. - Marouane Il Idrissi; Nicolas Bousquet 002; Fabrice Gamboa; Bertrand Iooss; Jean-Michel Loubes (J. Multivar. Anal., 2025)

The ENBIS-23 Quality and Reliability Engineering International Special Issue. - Bertrand Iooss; Christian H. Weiß (Qual. Reliab. Eng. Int., 2025)