1 citations · 1 across the 4 of their papers we have counts for
3 papers · 1 filter
Efficient multidisciplinary design via Bayesian optimization
Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage +3
This study introduces SEGOMOE, a Bayesian optimization tool for optimizing complex, computationally expensive systems, especially in aeronautics. It efficiently handles mixed desig…
Transfer Learning in Bayesian Optimization for Aircraft Design
Ali Tfaily, Youssef Diouane, Nathalie Bartoli +1
The use of transfer learning within Bayesian optimization addresses the disadvantages of the so-called \textit{cold start} problem by using source data to aid in the optimization o…
Multi-fidelity approaches for general constrained Bayesian optimization with application to aircraft design
Oihan Cordelier, Youssef Diouane, Nathalie Bartoli +1
Aircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization problems. In this context, there has been growing interest…