| Dicekriging, Diceoptim: Two R packages for the analysis of computer experiments by kriging-based metamodelling and optimization O Roustant, D Ginsbourger, Y Deville Journal of Statistical Software 51 (1), 54p, 2012 | 648 | 2012 |
| Kriging is well-suited to parallelize optimization D Ginsbourger, R Le Riche, L Carraro Computational intelligence in expensive optimization problems, 131-162, 2010 | 487* | 2010 |
| Sequential design of computer experiments for the estimation of a probability of failure J Bect, D Ginsbourger, L Li, V Picheny, E Vazquez Statistics and Computing 22 (3), 773–793, 2012 | 324 | 2012 |
| A benchmark of kriging-based infill criteria for noisy optimization V Picheny, T Wagner, D Ginsbourger Structural and multidisciplinary optimization 48 (3), 607-626, 2013 | 314 | 2013 |
| Adaptive designs of experiments for accurate approximation of a target region V Picheny, D Ginsbourger, O Roustant, RT Haftka, NH Kim | 301 | 2010 |
| Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision V Picheny, D Ginsbourger, Y Richet, G Caplin Technometrics 55 (1), 2-13, 2013 | 199 | 2013 |
| Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set C Chevalier, J Bect, D Ginsbourger, E Vazquez, V Picheny, Y Richet Technometrics 56 (4), 455-465, 2014 | 147 | 2014 |
| Fast computation of the multi-points expected improvement with applications in batch selection C Chevalier, D Ginsbourger International Conference on Learning and Intelligent Optimization, 59-69, 2013 | 134 | 2013 |
| Additive covariance kernels for high-dimensional Gaussian process modeling N Durrande, D Ginsbourger, O Roustant Annales de la faculté des sciences de Toulouse Mathématiques 21 (3), 481-499, 2012 | 115* | 2012 |
| ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis N Durrande, D Ginsbourger, O Roustant, L Carraro Journal of Multivariate Analysis 115, 57-67, 2013 | 85 | 2013 |
| Expected improvements for the asynchronous parallel global optimization of expensive functions: Potentials and challenges J Janusevskis, RL Riche, D Ginsbourger, R Girdziusas International Conference on Learning and Intelligent Optimization, 413-418, 2012 | 75* | 2012 |
| On uncertainty quantification in hydrogeology and hydrogeophysics N Linde, D Ginsbourger, J Irving, F Nobile, A Doucet Advances in Water Resources 110, 166-181, 2017 | 71 | 2017 |
| Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations M Binois, D Ginsbourger, O Roustant European journal of operational research 243 (2), 386-394, 2015 | 67 | 2015 |
| A supermartingale approach to Gaussian process based sequential design of experiments J Bect, F Bachoc, D Ginsbourger Bernoulli 25 (4A), 2883-2919, 2019 | 65 | 2019 |
| Multiples metamodeles pour l'approximation et l'optimisation de fonctions numeriques multivariables D Ginsbourger Ecole Nationale Supérieure des Mines de Saint-Etienne, 2009 | 62* | 2009 |
| Towards Gaussian process-based optimization with finite time horizon D Ginsbourger, RL Riche mODa 9–Advances in Model-Oriented Design and Analysis, 89-96, 2010 | 61 | 2010 |
| Differentiating the multipoint expected improvement for optimal batch design S Marmin, C Chevalier, D Ginsbourger International workshop on machine learning, optimization and big data, 37-48, 2015 | 59 | 2015 |
| Dealing with asynchronicity in parallel Gaussian process based global optimization D Ginsbourger, J Janusevskis, R Le Riche Technical Report, 2010 | 59 | 2010 |
| Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package V Picheny, D Ginsbourger Computational Statistics & Data Analysis 71, 1035-1053, 2014 | 51 | 2014 |
| A note on the choice and the estimation of kriging models for the analysis of deterministic computer experiments D Ginsbourger, D Dupuy, A Badea, L Carraro, O Roustant Applied Stochastic Models in Business and Industry 25 (2), 115-131, 2009 | 48 | 2009 |
Olivier RoustantProfessor, INSA Toulouse, FranceVerified email at insa-toulouse.fr
