| Efficient global optimization of constrained mixed variable problems J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin Journal of Global Optimization 73 (3), 583-613, 2019 | 61 | 2019 |
| Bayesian optimization of variable-size design space problems J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin Optimization and Engineering 22 (1), 387-447, 2021 | 38 | 2021 |
| Overview and comparison of gaussian process-based surrogate models for mixed continuous and discrete variables: application on aerospace design problems J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin High-Performance Simulation-Based Optimization, 189-224, 2020 | 32 | 2020 |
| How to deal with mixed-variable optimization problems: An overview of algorithms and formulations J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin World Congress of Structural and Multidisciplinary Optimisation, 64-82, 2017 | 19 | 2017 |
| Coupling and selecting constraints in Bayesian optimization under uncertainties J Pelamatti, R Le Riche, C Helbert, C Blanchet-Scalliet | 5 | 2022 |
| Surrogate model based optimization of constrained mixed variable problems: application to the design of a launch vehicle thrust frame J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin AIAA Scitech 2019 Forum, 1971, 2019 | 5 | 2019 |
| Mixed-variable Bayesian optimization: application to aerospace system design J Pelamatti Université de Lille, 2020 | 4 | 2020 |
| Mixed Variable Gaussian Process-Based Surrogate Modeling Techniques: Application to Aerospace Design J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin Journal of Aerospace Information Systems 18 (11), 813-837, 2021 | 3 | 2021 |
| Learning functions defined over sets of vectors with kernel methods B Sow, R Le Riche, J Pelamatti, S Zannane, M Keller 5 th ECCOMAS Thematic Conference on Uncertainty Quantification in …, 2023 | 2 | 2023 |
| Mdo related issues: Multi-objective and mixed continuous/discrete optimization L Brevault, J Pelamatti, A Hebbal, M Balesdent, EG Talbi, N Melab Aerospace System Analysis and Optimization in Uncertainty, 321-358, 2020 | 2 | 2020 |
| Fiches pédagogiques sur le traitement des incertitudes dans les codes de calcul JB Blanchard, R Chocat, G Damblin, M Baudin, N Bousquet, V Chabridon, ... EDF, 2023 | | 2023 |
| Cloud of points as discrete measures for Gaussian models and stochastic optimization B Sow, R Le Riche, S Zannane, M Keller, J Pelamatti MASCOT-NUM2023, 2023 | | 2023 |
| Gaussian Processes Indexed by Clouds of Points: a study Babacar SOW (EMSE, LIMOS), Rodolphe LE RICHE (CNRS, LIMOS) B Sow, R Le Riche, J Pelamatti, S Zannane, M Keller MASCOT-NUM, 2022 | | 2022 |
| Sampling Criteria for Constrained Bayesian Optimization under Uncertainty J Pelamatti, MR El Amri, R Le Riche, C Blanchet-Scalliet, C Helbert Hybrid Conference: 2022 SIAM Conference on Uncertainty Quantification, 2022 | | 2022 |
| Coupling and selecting constraints in Bayesian optimization under uncertainties J Pelamatti, R Le Riche, C Helbert, C Blanchet-Scalliet arXiv e-prints, arXiv: 2204.00527, 2022 | | 2022 |
| Coupling constraints in Bayesian optimization with uncertainties R El Amri, J Pelamatti, R Le Riche, C Helbert, C Blanchet-Scalliet 4th International Conference on Uncertainty Quantification in Computational …, 2021 | | 2021 |
| Coupling constraints in Bayesian optimization with uncertainties J Pelamatti, R Le Riche, C Helbert, C Blanchet-Scalliet Journées scientifiques d'automne de la chaire OQUAIDO, 2020 | | 2020 |
| Optimisation Bayésienne mixte: Application à la conception de véhicules aérospatiaux J Pelamatti | | 2020 |
| Mixed-variable Bayesian optimization J Pelamatti INRIA Lille, 2020 | | 2020 |
| Overview and Comparison of Gaussian Process-Based Surrogate Models for Mixed Continuous and Discrete J Pelamatti, L Brevault, M Balesdent, EG Talbi, Y Guerin High-Performance Simulation-Based Optimization 833, 189, 2019 | | 2019 |
