42 citations · 68 across the 7 of their papers we have counts for
8 papers
LAT: a Latinized aperiodic tiling for any sample size
Pamphile T. Roy
Quasi-Monte Carlo methods allow computer experiments to be run with far fewer simulations than crude Monte Carlo. A digital net in base two, such as Sobol', is however only balance…
Improving Discrepancy Measures for Global Sensitivity Analysis
Samuele Lo Piano, Alessio Lachi, Razi Sheikholeslami +3
Sensitivity analysis methods based on Sobol' total-order indices () are well-founded but computationally demanding. A recently proposed ersatz discrepancy measure offers a che…
Discrepancy measures for sensitivity analysis
Arnald Puy, Pamphile T. Roy, Andrea Saltelli
While sensitivity analysis improves the transparency and reliability of mathematical models, its uptake by modelers is still scarce. This is partially explained by its technical re…
Newcomb-Benford's law as a fast ersatz of discrepancy measures
Pamphile T. Roy
Thanks to the increasing availability in computing power, high-dimensional engineering problems seem to be at reach. But the curse of dimensionality will always prevent us to try o…
Reconstruction of Hydraulic Data by Machine Learning
Corentin J. Lapeyre, Nicolas Cazard, Pamphile T. Roy +2
Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (charac…
Sounding Spider: An Efficient Way for Representing Uncertainties in High Dimensions
Pamphile T. Roy, Sophie Ricci, Bénédicte Cuenot +1
This article proposes a visualization method for multidimensional data based on: (i) Animated functional Hypothetical Outcome Plots (f-HOPs); (ii) 3-dimensional Kiviat plot; and (i…
Resampling Strategies to Improve Surrogate Model-based Uncertainty Quantification - Application to LES of LS89
Pamphile Tupui Roy, Luis Miguel Segui, Jean-Christophe Jouhaud +1
Uncertainty Quantification (UQ) is receiving more and more attention for engineering applications in particular from robust optimization. Indeed, running a computer experiment only…
Comparison of Polynomial Chaos and Gaussian Process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows
Pamphile Tupui Roy, Nabil El Moçayd, Sophie Ricci +4
Data assimilation is widely used to improve flood forecasting capability, especially through parameter inference requiring statistical information on the uncertain input parameters…