Nathalie Bartoli
Ph.D. Institut National des Sciences Appliquees de Toulouse 2000
Facts
7 properties- Instance of
- human
- Doctoral advisor
- Abderrahmane Bendali[3]
- Doctoral student
- Wikidata item[5]
🏷️ Also known as
en Nathalie Bartoli
🔖 Identifiers · 10
- ISNI
- 0000000001078601
- ORCID iD
- 0000-0002-6451-2203
- VIAF cluster ID
- 54361358
- Bibliothèque nationale de France ID
- 14408281q
- Described at URL
- www.onera.fr
- HAL author ID
- nathalie-bartoli
- IdRef ID
- 059362855
- MR Author ID
- 670020
- Mathematics Genealogy Project ID
- 222204
- Scopus author ID
- 6506986208
🔗 Connections
Author of 8
An Improved Approach for Estimating the Hyperparameters of the Kriging Model for High-Dimensional Problems through the Partial Least Squares Method,
A Python surrogate modeling framework with derivatives,
Bayesian optimization with hidden constraints for aircraft design,
Disciplinary proper orthogonal decomposition and interpolation for the resolution of parameterized multidisciplinary analysis,
Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design,
SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes,
Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm,
Upper trust bound feasibility criterion for mixed constrained Bayesian optimization with application to aircraft design
← Authored by 8
An Improved Approach for Estimating the Hyperparameters of the Kriging Model for High-Dimensional Problems through the Partial Least Squares Method,
A Python surrogate modeling framework with derivatives,
Bayesian optimization with hidden constraints for aircraft design,
Disciplinary proper orthogonal decomposition and interpolation for the resolution of parameterized multidisciplinary analysis,
Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design,
SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes,
Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm,
Upper trust bound feasibility criterion for mixed constrained Bayesian optimization with application to aircraft design
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FAQs
Where did Nathalie Bartoli go to school?
Nathalie Bartoli was educated at Institut national des sciences appliquées de Toulouse[2].