| Derivative-based global sensitivity measures and their link with Sobol’sensitivity indices S Kucherenko, S Song Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April …, 2016 | 536* | 2016 |
| Estimating the approximation error when fixing unessential factors in global sensitivity analysis S Tarantola, D Gatelli, SS Kucherenko, W Mauntz Reliability engineering & system safety 92 (7), 957-960, 2007 | 415 | 2007 |
| Estimation of global sensitivity indices for models with dependent variables S Kucherenko, S Tarantola, P Annoni Computer physics communications 183 (4), 937-946, 2012 | 362 | 2012 |
| Monte Carlo evaluation of derivative-based global sensitivity measures S Kucherenko, M Rodriguez-Fernandez, C Pantelides, N Shah Reliability Engineering & System Safety 94 (7), 1135-1148, 2009 | 334 | 2009 |
| The future of sensitivity analysis: an essential discipline for systems modeling and policy support S Razavi, A Jakeman, A Saltelli, C Prieur, B Iooss, E Borgonovo, ... Environmental Modelling & Software 137, 104954, 2021 | 267 | 2021 |
| Construction and comparison of high‐dimensional Sobol'generators IM Sobol', D Asotsky, A Kreinin, S Kucherenko Wilmott 2011 (56), 64-79, 2011 | 215 | 2011 |
| Global sensitivity analysis challenges in biological systems modeling A Kiparissides, SS Kucherenko, A Mantalaris, EN Pistikopoulos Industrial & Engineering Chemistry Research 48 (15), 7168-7180, 2009 | 168 | 2009 |
| The identification of model effective dimensions using global sensitivity analysis S Kucherenko, B Feil, N Shah, W Mauntz Reliability Engineering & System Safety 96 (4), 440-449, 2011 | 161 | 2011 |
| A model for the sintering of spherical particles of different sizes by solid state diffusion J Pan, H Le, S Kucherenko, JA Yeomans Acta materialia 46 (13), 4671-4690, 1998 | 157 | 1998 |
| Exploring multi-dimensional spaces: A comparison of Latin hypercube and quasi Monte Carlo sampling techniques S Kucherenko, D Albrecht, A Saltelli arXiv preprint arXiv:1505.02350, 2015 | 149 | 2015 |
| Application of deterministic low-discrepancy sequences in global optimization S Kucherenko, Y Sytsko Computational Optimization and Applications 30, 297-318, 2005 | 149 | 2005 |
| A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices S Kucherenko Computer Physics Communications 181 (7), 1212-1217, 2010 | 139 | 2010 |
| Comparison of deterministic and stochastic approaches to global optimization L Liberti, S Kucherenko International Transactions in Operational Research 12 (3), 263-285, 2005 | 105 | 2005 |
| On global sensitivity analysis of quasi-Monte Carlo algorithms. IM Sobol, SS Kucherenko Monte Carlo Methods Appl. 11 (1), 83-92, 2005 | 92 | 2005 |
| Finite element formulation of coupled grain-boundary and surface diffusion with grain-boundary migration J Pan, ACF Cocks, S Kucherenko Proceedings of the Royal Society of London. Series A: Mathematical, Physical …, 1997 | 89 | 1997 |
| Metamodelling with independent and dependent inputs MM Zuniga, S Kucherenko, N Shah Computer Physics Communications 184 (6), 1570-1580, 2013 | 77 | 2013 |
| Comparison of Monte Carlo and quasi Monte Carlo sampling methods in high dimensional model representation B Feil, S Kucherenko, N Shah 2009 first international conference on advances in system simulation, 12-17, 2009 | 61 | 2009 |
| Calculating first-order sensitivity measures: A benchmark of some recent methodologies D Gatelli, S Kucherenko, M Ratto, S Tarantola Reliability Engineering & System Safety 94 (7), 1212-1219, 2009 | 56 | 2009 |
| Derivative based global sensitivity measures IM Sobol, S Kucherenko Procedia-Social and Behavioral Sciences 2 (6), 7745-7746, 2010 | 54 | 2010 |
| Different numerical estimators for main effect global sensitivity indices S Kucherenko, S Song Reliability Engineering & System Safety 165, 222-238, 2017 | 51 | 2017 |
