User profiles for Paul Saves
 | Paul SavesIRIT, Université Toulouse Capitole Verified email at alumni.enac.fr Cited by 226 |
SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes
The Surrogate Modeling Toolbox (SMT) is an open-source Python package that offers a
collection of surrogate modeling methods, sampling techniques, and a set of sample problems. …
collection of surrogate modeling methods, sampling techniques, and a set of sample problems. …
Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design
AIAA SCITECH 2022 Forum: Multidisciplinary design optimization with mixed categorical
variables for aircraft design Page 1 Bayesian optimization for mixed variables using an …
variables for aircraft design Page 1 Bayesian optimization for mixed variables using an …
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft
Recently, there has been a growing interest in mixed-categorical metamodels based on
Gaussian Process (GP) for Bayesian optimization. In this context, different approaches can be …
Gaussian Process (GP) for Bayesian optimization. In this context, different approaches can be …
A mixed-categorical correlation kernel for Gaussian process
Recently, there has been a growing interest for mixed-categorical meta-models based on
Gaussian process (GP) surrogates. In this setting, several existing approaches use different …
Gaussian process (GP) surrogates. In this setting, several existing approaches use different …
A general square exponential kernel to handle mixed-categorical variables for Gaussian process
AIAA AVIATION 2022 Forum: A general square exponential kernel to handle mixed-categorical
variables for Gaussian process Page 1 A general square exponential kernel to handle …
variables for Gaussian process Page 1 A general square exponential kernel to handle …
Regularized infill criteria for multi-objective Bayesian optimization with application to aircraft design
… PhD Student, Information Processing and Systems Department & Complex Systems and
Engineering Department, paul.saves@onera.fr ∗∗Researcher, MDO group, Aircraft Design & …
Engineering Department, paul.saves@onera.fr ∗∗Researcher, MDO group, Aircraft Design & …
High-dimensional multidisciplinary design optimization for aircraft eco-design/Optimisation multi-disciplinaire en grande dimension pour l'\'eco-conception avion en …
P Saves - arXiv preprint arXiv:2402.04711, 2024 - arxiv.org
D e nos jours, un intérêt significatif et croissant pour améliorer les processus de conception
de véhicules s’ observe dans le domaine de l’optimisation multidisciplinaire grâce au …
de véhicules s’ observe dans le domaine de l’optimisation multidisciplinaire grâce au …
High-dimensional multidisciplinary design optimization for aircraft eco-design
P Saves - 2024 - hal.science
Description: Ph.D on Gaussian Process kernels for Bayesian optimization in high dimension
with mixed and hierarchical variables at ISAE-SUPAERO. Keywords: Gaussian process, …
with mixed and hierarchical variables at ISAE-SUPAERO. Keywords: Gaussian process, …
Surrogate-based optimization of system architectures subject to hidden constraints
System Architecture Optimization (SAO) can support the design of novel architectures by
formulating the architecting process as an optimization problem. The exploration of novel …
formulating the architecting process as an optimization problem. The exploration of novel …
System architecture optimization strategies: dealing with expensive hierarchical problems
Choosing the right system architecture for the problem at hand is challenging due to the large
design space and high uncertainty in the early stage of the design process. Formulating …
design space and high uncertainty in the early stage of the design process. Formulating …