11 citations · 52 across the 16 of their papers we have counts for
4 papers · 1 filter
High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings
Rémy Priem, Youssef Diouane, Nathalie Bartoli +2
Bayesian optimization (BO) is one of the most powerful strategies to solve computationally expensive-to-evaluate blackbox optimization problems. However, BO methods are conventiona…
System Architecture Optimization Strategies: Dealing with Expensive Hierarchical Problems
Jasper H. Bussemaker, Paul Saves, Nathalie Bartoli +2
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. Formulati…
High-dimensional multidisciplinary design optimization for aircraft eco-design / Optimisation multi-disciplinaire en grande dimension pour l'éco-conception avion en avant-projet
Paul Saves
The objective of this Philosophiae Doctor (Ph.D) thesis is to propose an efficient approach for optimizing a multidisciplinary black-box model when the optimization problem is cons…
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft
Paul Saves, Youssef Diouane, Nathalie Bartoli +2
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 u…