| Comparison of polynomial chaos and Gaussian process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows PT Roy, N El Moçayd, S Ricci, JC Jouhaud, N Goutal, M De Lozzo, ... Stochastic environmental research and risk assessment 32, 1723-1741, 2018 | 42 | 2018 |
| scipy/scipy: SciPy 1.9. 0 R Gommers, P Virtanen, E Burovski, W Weckesser, TE Oliphant, ... Zenodo, 2022 | 23 | 2022 |
| Design optimization of an heat exchanger using Gaussian process R Campet, PT Roy, B Cuenot, E Riber, JC Jouhaud International Journal of Heat and Mass Transfer 150, 119264, 2020 | 21 | 2020 |
| BATMAN: Statistical analysis for expensive computer codes made easy P T. Roy, S Ricci, R Dupuis, R Campet, JC Jouhaud, C Fournier The Journal of Open Source Software 3 (21), 493, 2018 | 21 | 2018 |
| Resampling strategies to improve surrogate model‐based uncertainty quantification: Application to LES of LS89 PT Roy, LM Segui, JC Jouhaud, L Gicquel International Journal for Numerical Methods in Fluids 87 (12), 607-627, 2018 | 18 | 2018 |
| Multifidelity modeling of irradiated particle-laden turbulence subject to uncertainty L Jofre, M Papadakis, PT Roy, A Aiken, G Iaccarino International Journal for Uncertainty Quantification 10 (6), 2020 | 13 | 2020 |
| Versatile sequential sampling algorithm using kernel density estimation PT Roy, L Jofre, JC Jouhaud, B Cuenot European Journal of Operational Research 284 (1), 201-211, 2020 | 10 | 2020 |
| Quasi-Monte Carlo Methods in Python PT Roy, AB Owen, M Balandat, M Haberland Journal of Open Source Software 8 (84), 5309, 2023 | 7 | 2023 |
| scipy/scipy: SciPy 1.7. 3 R Gommers, P Virtanen, E Burovski, TE Oliphant, W Weckesser, ... Zenodo, 2021 | 5 | 2021 |
| Reconstruction of hydraulic data by machine learning CJ Lapeyre, N Cazard, PT Roy, S Ricci, F Zaoui Advances in Hydroinformatics: SimHydro 2019-Models for Extreme Situations …, 2020 | 5 | 2020 |
| statsmodels/statsmodels: Release 0.14. 1 J Perktold, S Seabold, K Sheppard, K Shedden, P Quackenbush, ... Zenodo, 2023 | 4 | 2023 |
| Simple binning algorithm and SimDec visualization for comprehensive sensitivity analysis of complex computational models M Kozlova, A Ahola, PT Roy, JS Yeomans arXiv preprint arXiv:2310.13446, 2023 | 2 | 2023 |
| Sounding spider: An efficient way for representing uncertainties in high dimensions PT Roy, S Ricci, B Cuenot, JC Jouhaud arXiv preprint arXiv:1808.01217, 2018 | 2 | 2018 |
| An annotated timeline of sensitivity analysis S Tarantola, F Ferretti, SL Piano, M Kozlova, A Lachi, R Rosati, A Puy, ... Environmental Modelling & Software 174, 105977, 2024 | 1 | 2024 |
| Discrepancy measures for sensitivity analysis in mathematical modeling A Puy, A Saltelli arXiv preprint arXiv:2206.13470, 2022 | 1 | 2022 |
| Uncertainty Quantification-Driven Robust Design Assessment of a Swirler’s Geometry PT Roy, G Daviller, JC Jouhaud, B Cuenot Paris-Saclay: SAFRAN TECH. https://www. researchgate. net/publication …, 2017 | 1 | 2017 |
| Simulation Decomposition in Python PT Roy, M Kozlova Journal of Open Source Software 9 (98), 6713, 2024 | | 2024 |
| Discrepancy measures for global sensitivity analysis A Puy, PT Roy, A Saltelli Technometrics, 1-19, 2024 | | 2024 |
| Discrepancy measures for sensitivity analysis A Puy, PT Roy, A Saltelli arXiv preprint arXiv:2206.13470, 2022 | | 2022 |
| Newcomb-Benford's law as a fast ersatz of discrepancy measures PT Roy arXiv preprint arXiv:2103.08705, 2021 | | 2021 |
nicole goutalEDF R&D在 edf.fr 的电子邮件经过验证
