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06/02/2023
Shapley effects and proportional marginal effects for global sensitivity analysis: application to computed tomography scan organ dose estimation
Concerns have been raised about possible cancer risks after exposure to ...
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05/12/2023
A comparison between Bayesian and ordinary kriging based on validation criteria: application to radiological characterisation
In decommissioning projects of nuclear facilities, the radiological char...
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03/18/2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensive...
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01/06/2023
On the coalitional decomposition of parameters of interest
Understanding the behavior of a black-box model with probabilistic input...
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10/24/2022
Proportional marginal effects for global sensitivity analysis
Performing (variance-based) global sensitivity analysis (GSA) with depen...
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09/23/2022
Quantile-constrained Wasserstein projections for robust interpretability of numerical and machine learning models
Robustness studies of black-box models is recognized as a necessary task...
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07/08/2022
Model predictivity assessment: incremental test-set selection and accuracy evaluation
Unbiased assessment of the predictivity of models learnt by supervised m...
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07/01/2021
Global sensitivity analysis using derivative-based sparse Poincaré chaos expansions
Variance-based global sensitivity analysis, in particular Sobol' analysi...
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04/27/2021
Sample selection from a given dataset to validate machine learning models
The selection of a validation basis from a full dataset is often require...
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01/20/2021
Developments and applications of Shapley effects to reliability-oriented sensitivity analysis with correlated inputs
Reliability-oriented sensitivity analysis methods have been developed fo...
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08/07/2020
An information geometry approach for robustness analysis in uncertainty quantification of computer codes
Robustness analysis is an emerging field in the domain of uncertainty qu...
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04/08/2020
Statistical identification of penalizing configurations in high-dimensional thermalhydraulic numerical experiments: The ICSCREAM methodology
In the framework of risk assessment in nuclear accident analysis, best-e...
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02/26/2020
A Visual Sensitivity Analysis for Parameter-Augmented Ensembles of Curves
Engineers and computational scientists often study the behavior of their...
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01/31/2020
A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping
An original graph clustering approach to efficient localization of error...
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10/11/2019
Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation
In order to leverage the information embedded in the background state an...
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05/10/2019
Large scale in transit computation of quantiles for ensemble runs
The classical approach for quantiles computation requires availability o...
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01/22/2019
Optimal Uncertainty Quantification of a risk measurement from a thermal-hydraulic code using Canonical Moments
We study an industrial computer code related to nuclear safety. A major ...
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12/29/2018
Advanced methodology for uncertainty propagation in computer experiments with large number of inputs
In the framework of the estimation of safety margins in nuclear accident...
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11/30/2018
