Bertrand Iooss

• J-F Wald and B. Iooss, Uncertainty quantification and metamodeling of multi-fidelity CFD computation of a heated fuel assembly, In preparation

​

• B.B. Ketema, R. Sueur, B. Iooss, N. Bousquet, F. Gamboa and F. Constantino, Fisher-Rao distance between truncated distributions and robustness analysis in uncertainty quantification, Preprint - ArXiV version

 

• E. Jaber, V. Blot, N. Brunel, V. Chabridon, E. Remy, B. Iooss, D. Lucor, M. Mougeot and A. Leite, Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees, Preprint - HAL version -

 

• M. Il Idrissi, N. Bousquet, F. Gamboa, B. Iooss and J-M. Loubès, Hoeffding decomposition of black-box models with dependent inputs, Preprint - HAL version

​

• A. Foucault, M. Il Idrissi, B. Iooss, M-O. Bernier and S. Ancelet, A global sensitivity analysis of organ dose estimation following computed tomography scans, Preprint - HAL version - codes

​

• L. Clouvel, V. Chabridon, B. Iooss, M. Il Idrissi and F. Robin, An overview of variance-based importance measures in the linear regression context: comparative analyses and numerical tests, Preprint - HAL version - codes

​

​

​

​

​

​

​

​

​

• M. Il Idrissi, N. Bousquet, F. Gamboa, B. Iooss and J-M. Loubès, Quantile-constrained Wasserstein projections for robust interpretability analyses of numerical and machine learning models, Electronic Journal of Statistics, 18:2721–2770, 2024 - paper - HAL version - codes

 

• M. Herin, M. Il Idrissi, V. Chabridon and B. Iooss, Proportional marginal effects for global sensitivity analysis, SIAM/ASA Journal of Uncertainty Quantification, 12:667-692 2024 - paper - HAL version - codes

 

• A. Marrel and B. Iooss, Probabilistic surrogate modeling by Gaussian process: A new estimation algorithm for more reliable prediction, Reliability Engineering and System Safety, 247:110120, 2024 - paper - HAL version

​

• A. Marrel and B. Iooss, Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation, Reliability Engineering and System Safety, 247:110094, 2024 - paper - HAL version

​

• E. Jaber, V. Chabridon, E. Remy, M. Baudin, D. Lucor, M. Mougeot B. Iooss, Sensitivity analysis of a multi-physics long-term clogging model for steam generator, International Journal for Uncertainty Quantification, 2024, DOI:10.1615/Int.J.UncertaintyQuantification.2024051489, paper - HAL version

 

• E. Fekhari, V. Chabridon, J. Muré and B. Iooss, Given-data probabilistic fatigue assessment for offshore wind turbines using Bayesian quadrature, Data Centric Engineering, 5:e5, 2024 - paper - HAL version - codes

​

• J. Baccou, T. Glantz, A. Ghione, L. Sargentini, P. Fillion, G. Damblin, R. Sueur, B. Iooss, J. Fang, J. Liu, C. Yang, Y. Zheng, A. Ui, M. Saito, R. Mendizábal Sanz, A. Bersano, F. Mascari, T. Skorek, L. Tiborcz, Y. Hirose, T. Takeda, H. Nakamura, C. Choi, J. Heo, A. Petruzzi, K. Zeng, Z. Xie, X. Wu, H. Eguchi,  F. Pangukir, P. Breijder, S. Franssen, G. Perret, I.D. Clifford, T.M. Coscia, F. Di Maio, E. Zio, N. Pedroni, J. Zhang, J. Freixa, F. Rizzo, C. Ciurluini, F. Giannetti and M. Adorni, A systematic approach for the adequacy analysis of a set of experimental databases: Application in the framework of the ATRIUM project, Nuclear Engineering and Design, 421:113035, 2024 - paper

​

• M. Wieskotten, M. Crozet, B. Iooss, C. Lacaux and A. Marrel, A comparison between Bayesian and ordinary kriging based on validation criteria: application to radiological characterisation, Mathematical Geosciences, 56:143–168, 2024 - paper - view-only version - HAL version - codes

​

• M. Il Idrissi, N. Bousquet, F. Gamboa, B. Iooss and J-M. Loubès, On the coalitional decomposition of parameters of interest, Comptes Rendus Mathématiques de l'Académie des Sciences, Comptes Rendus Mathématique, 361:1653-1662, 2023 - paper - HAL version

​

• L. Lefebvre, M. Segond, R. Spaggiari, L. Le Gratiet, E. Deri, B. Iooss and G. Damblin, Improving the predictivity of a steam generator clogging numerical model by global sensitivity analysis and Bayesian calibration techniques, Nuclear Science and Engineering, 197:2136–2149, 2023 - paper

​

• N. Lüthen, O. Roustant, F. Gamboa, B. Iooss, S. Marelli and B. Sudret, Global sensitivity analysis using derivative-based sparse Poincaré chaos expansions, International Journal for Uncertainty Quantification, 13(6):57–82, 2023 - paper, HAL version - ArXiV version

 

• S. Cheng, C. Quilodran-Casas, S. Ouala, A. Farchi, C. Liu, O. Tandeo, R. Fablet, D. Lucor, B. Iooss, J. Brajard, D. Xiao, T. Pfander, W. Ding, Y. Guo, A. Carrassi, M. Bocquet and R. Arcucci, Machine Learning with data assimilation and uncertainty quantification for dynamical systems: a review, IEEE/CAA Journal of Automatica Sinica, 10(6):1361-1387, 2023 - paper, ArXiV version

​

• A. Ajenjo, E. Ardillon, V. Chabridon, B. Iooss, S. Cogan, E. Sadoulet-Reboul, An info-gap framework for robustness assessment of epistemic uncertainty models in hybrid structural reliability analysis, Structural Safety, 96, 102196, 2022 - paper - HAL version

​

• A. Marrel, B. Iooss and V. Chabridon, The ICSCREAM methodology: Identification of penalizing configurations in computer experiments using screening and metamodel – Applications in thermal-hydraulics, Nuclear Science and Engineering, 196:301-321, 2022 - free eprint - paper - HAL version

​

• C. Demay, B. Iooss, L. Le Gratiet and A. Marrel, Model selection for Gaussian Process regression: an application with highlights on the predictive variance, Quality and Reliability Engineering International Journal, 38:1482-1500, 2022 - paper - HAL ref

​

• C. Gauchy and J. Stenger and R. Sueur and B. Iooss, An information geometry approach for robustness analysis in uncertainty quantification of computer codes, Technometrics, 64:80-91, 2022 - paper - HAL version - codes

​

• B. Iooss, V. Vergès and V. Larget, BEPU robustness analysis via perturbed-law based sensitivity indices, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 236:855-865, 2022 - paper - HAL version

​

• M. Il Idrissi, V. Chabridon and B. Iooss, Developments and applications of Shapley effects to reliability-oriented sensitivity analysis with correlated inputs, Environmental Modelling & Software, 143, 105115, 2021 - paper - HAL version - codes

​

• A. Rollón de Pinedo, M. Couplet, B. Iooss, N. Marie, A. Marrel, E. Merle and R. Sueur, Time-dependent Outlier Detection by means of h-mode depth and dynamic time warping, Applied Sciences, Applied Sciences 2021, 11(23), 11475 - paper - HAL version

​

• S. Cheng, J-P. Argaud, B. Iooss, D. Lucor and A. Ponçot, A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping, Mathematical Geosciences, 53:1751–1780, 2021 - paper - HAL version

​

• S. Razavi, A. Jakeman, A. Saltelli, C. Prieur, B. Iooss, E. Borgonovo, E. Plischke, S. Lo Piano, W. Becker, S. Tarantola, J. Guillaume, J. Jakeman, H.  Gupta, T. Iwanaga, N. Melillo, G. Rabitti, V. Chabridon, Q. Duan, X. Sun,  R. Sheikholeslami, M. Asadzadeh, S. Kucherenko, The Future of Sensitivity Analysis: An Essential Discipline for Systems Modelling and Policy Making, Environmental Modelling & Software, 137, 104954, 2021 - paper - HAL ref

​

• S. Cheng, J-P. Argaud, B. Iooss, D. Lucor and A. Ponçot, Error covariance tuning in variational data assimilation: application to an operating hydrological model, Stochastic Environmental Research and Risk Assessment, 35:1019-1038, 2021 - paper - HAL version

​

• E. Le Mire, E. Burger, B. Iooss and C. Mai, Prediction of crack propagation kinetics through multipoint stochastic simulations of microscopic fields, The European Journal of Physics - Nuclear Sciences & Technology (EPJ-N), 7, 4, 2021 - paper - HAL version

​

• J. Baccou, J. Zhang, P. Fillion, G. Damblin, A. Petruzzi, R. Mendizábal, F. Reventós, T. Skorek, M. Couplet, B. Iooss, D. Oh and T. Takeda, SAPIUM: a generic framework for a practical and transparent quantification of thermal hydraulic code model input uncertainty, Nuclear Science and Engineering, 194 (8-9), 721-736, 2020 - paper

​

• J. Stenger, F. Gamboa, M. Keller and B. Iooss, Optimal uncertainty quantification of a risk measurement from a thermal-hydraulic code using canonical moments, International Journal for Uncertainty Quantification, 10:35-53, 2020 - paper - HAL version - codes

​

• O. Roustant, F. Gamboa and B. Iooss, Parseval inequalities and lower bounds for variance-based sensitivity indices, Electronic Journal of Statistics, 14:386-412, 2020 - paper - HAL version

​

• A. Ribés, J. Pouderoux and B. Iooss, A Visual Sensitivity Analysis for Parameter-Augmented Ensembles of Curves, The Journal of Verification, Validation and Uncertainty Quantification (VVUQ), 4(4): 041007, 2019 - paper - repository for reproducibility materials - HAL version

​

• B. Iooss and C. Prieur, Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications, International Journal for Uncertainty Quantification, 9:493-514, 2019 - paper - HAL version

​

• S. Cheng, J-P. Argaud, B. Iooss, D. Lucor and A. Ponçot, Background error covariance iterative updating with invariant observation measures for data assimilation, Stochastic Environmental Research and Risk Assessment, 33:2033-2051, 2019 - paper - HAL version

​

• B. Iooss and A. Marrel, Advanced methodology for uncertainty propagation in computer experiments with large number of inputs, Nuclear Technology, 205:1588-1606, 2019 - paper - HAL version

​

• J. Baccou, J. Zhang, P. Fillion, G. Damblin, A. Petruzzi, R. Mendizábal, F. Reventós, T. Skorek, M. Couplet, B. Iooss, D. Oh and T. Takeda, Development of good practice guidance for quantification of thermal-hydraulic code model input uncertainty, Nuclear Engineering and Design, 354, 110173, 2019 - paper

​

• B. Iooss and L. Le Gratiet. Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes. Reliability Engineering and System Safety, 187:58-66, 2019 - paper - HAL version

​

• O. Roustant, F. Barthe and B. Iooss. Poincaré inequalities on intervals - application to sensitivity analysis. Electronic Journal of Statistics, Vol. 11, No. 2, 3081-3119, 2017. paper - HAL version

​

• G. Blatman, T. Delage, B. Iooss and N. Pérot. Probabilistic risk bounds for the characterization of radiological contamination. The European Journal of Physics - Nuclear Sciences & Technology (EPJ-N) 3, 23, 2017. paper - HAL version

​

• L. Le Gratiet, B. Iooss, G. Blatman, T. Browne, S. Cordeiro and B. Goursaud. Model assisted probability of detection curves: New statistical tools and progressive methodology. Journal of Nondestructive Evaluation, 36:8, 2017. paper - HAL version

​

• T. Browne, B. Iooss, L. Le Gratiet, J. Lonchampt and E. Remy. Stochastic simulators based optimization by Gaussian process metamodels - Application to maintenance investments planning issues. Quality and Reliability Engineering International Journal, 32:2067-2080, 2016. paper - HAL version

​

• T. Labopin-Richard, F. Gamboa, A. Garivier and B. Iooss. Bregman superquantiles. Estimation methods and applications. Dependence Modeling, 4:76-108, 2016. paper - HAL version

​

• P. Lemaître, E. Sergienko, A. Arnaud, N. Bousquet, F. Gamboa and B. Iooss. Density modification based reliability sensitivity analysis. Journal of Statistical Computation and Simulation, 85:1200-1223, 2015. paper - HAL version

​

• L. Le Gratiet, C. Cannamela and B. Iooss. A Bayesian approach for global sensitivity analysis of (multifidelity) computer codes. SIAMSA Journal of Uncertainty Quantification, 2:336-363, 2014. paper - HAL version

​

• O. Roustant, J. Fruth, B. Iooss and S. Kuhnt. Crossed-Derivative Based Sensitivity Measures for Interaction Screening. Mathematics and Computers in Simulation, 105:105-118, 2014. paper - HAL version

​

• S. Kucherenko, B. Delpuech, B. Iooss, S. Tarantola. Application of the control variate technique to estimation of total sensitivity indices. Reliability Engineering and System Safety, 134:251-259, 2014. paper

​

• G. Damblin, M. Couplet and B. Iooss. Numerical studies of space filling designs: optimization of Latin hypercube samples and subprojection properties. Journal of Simulation, 7:276-289, 2013. paper - HAL version

​

• M. Lamboni, B. Iooss, A-L. Popelin and F. Gamboa. Derivative-based global sensitivity measures: general links with Sobol' indices and numerical tests. Mathematics and Computers in Simulation, 87:45-54, 2013. paper - arxivversion

​

• A. Marrel, B. Iooss, S. da Veiga and M. Ribatet. Global sensitivity analysis of stochastic computer models with joint metamodels. Statistics and Computing, 22:833-847, 2012. paper - HAL version

​

• B. Auder, A. de Crecy, B. Iooss and M. Marquès. Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations. Reliability Engineering and System Safety, 107:122-131, 2012. paper - HAL version

​

• B. Iooss. Revue sur l'analyse de sensibilité globale de modèles numériques. Journal de la Société Française de Statistique, 152:1-23, 2011. paper

​

• A. Allard, N. Fischer, F. Didieux, E. Guillaume and B. Iooss. Evaluation of the most influent input variables on quantities of interest in a fire simulation. Journal de la Société Française de Statistique, 152:103-117, 2011. paper

​

• A. Marrel, B. Iooss, M. Jullien, B. Laurent and E. Volkova. Global sensitivity analysis for models with spatially dependent outputs. Environmetrics, 22:383-397, 2011. paper - arxiv version

​

• O. Asserin, A. Loredo, M. Petelet and B. Iooss. Global sensitivity analysis in welding simulations - What are the material data you really need? Finite Elements in Analysis and Design, 47:1004-1016, 2011. paper - HAL version

​

• G. Lorenzo, P. Zanocco, M. Giménez, M.Marquès, B. Iooss, R. Bolado Lavin, F. Pierro, G. Galassi, F. D’Auria and L. Burgazzi. Assessment of an isolation condenser of an integral reactor in view of uncertainties in engineering parameters. Science and Technology of Nuclear Installations, Volume Article ID 827354, 9 pages, doi:10.1155/2011/827354. paper

​

• M. Petelet, B. Iooss, O. Asserin and A. Loredo. Latin hypercube sampling with inequality constraints. Advances in Statistical Analysis, 94:325-339, 2010. paper - arxiv version

​

• B. Iooss, L. Boussouf, V. Feuillard and A. Marrel. Numerical studies of the metamodel fitting and validation processes. International Journal of Advances in Systems and Measurements, 3:11-21, 2010

​

• B. Iooss and M. Ribatet. Global sensitivity analysis of computer models with functional inputs. Reliability Engineering and System Safety, 94:1194-1204, 2009. paper - HAL version

​

• A. Marrel, B. Iooss, B. Laurent and O. Roustant. Calculations of Sobol indices for the Gaussian process metamodel. Reliability Engineering and System Safety, 94:742-751, 2009. paper - HAL version

​

• C. De Saint Jean, G. Noguere, B. Habert and B. Iooss. A Monte Carlo approach of nuclear model parameters uncertainties propagation. Nuclear Science and Engineering, 161:363-370, 2009. paper

​

• C. Cannamela, J. Garnier and B. Iooss. Controlled stratification for quantile estimation. Annals of Applied Statistics, 2:1554-1580, 2008. paper - arxiv version

​

• A. Marrel, B. Iooss, F. Van Dorpe and E. Volkova. An efficient methodology for modeling complex computer codes with Gaussian processes. Computational Statistics and Data Analysis, 52:4731-4744, 2008. paper - HAL version

​

• E. Volkova, B. Iooss and F. Van Dorpe. Global sensitivity analysis for a numerical model of radionuclide migration from the ``RRC Kurchatov Institute'' radwaste disposal site. Stochastic Environmental Research and Risk Assessment, 22:17-31, 2008. paper

​

• G. Noguere, D. Bernard, C. De Saint Jean, F. Gunsing, B. Iooss, K. Kobayashi, S. Mughabghab and P. Siegler. Propagation of the Np237 nuclear data uncertainties in integral calculations by Monte-Carlo techniques. Nuclear Science and Engineering, 160:108-122, 2008. paper

​

• F. Van Dorpe, B. Iooss, V. Semenov, O. Sorokovikova, A. Fokin and Y. Margerit. Atmospheric transport modeling with 3D Lagrangian dispersion codes compared with SF6 tracer experiments at regional scale. Science and Technology of Nuclear Installations, Volume 2007 (2007), Article ID 30863, 13 pages, doi:10.1155/2007/30863. paper

​

• B. Iooss, F. Van Dorpe and N. Devictor. Response surfaces and sensitivity analyses for an environmental model of dose calculations. Reliability Engineering and System Safety, 91:1241-1251, 2006. paper

​

• B. Iooss, D. Geraets, T. Mukerji, Y. Samuelides, M. Touati and A. Galli. Inferring the statistical distribution of velocity heterogeneities by statistical traveltime tomography. Geophysics, 68(5):1714-1730, 2003. paper

​

• B. Iooss, C. Lhuillier and H. Jeanneau. Numerical simulation of transit-time ultrasonic flowmeters: uncertainties due to fluid turbulence. Ultrasonics, 40:1009-1015, 2002. paper

​

• B. Iooss, Ph. Blanc-Benon and C. Lhuillier. Statistical moments of travel times at second order in isotropic and anisotropic random media. Waves in Random Media, 10:381-394, 2000. paper

​

• M. Touati, B. Iooss and A. Galli. Quantitative control of migration: a geostatistical attempt. Mathematical Geology, 31:277-295, 1999. paper

​

• B. Iooss. Seismic reflection traveltimes in two-dimensional statistically anisotropic random media. Geophysical Journal International, 135:999-1010, 1998. paper

​