5 citations · 6 across the 3 of their papers we have counts for
3 papers
PFEM-GP-dPHS : a finite element framework for combining Gaussian processes and infinite-dimensional port-Hamiltonian systems
Florian Courteville, Iain Henderson, Denis Matignon +1
In order to learn distributed port-Hamiltonian systems (dPHS) using Gaussian processes (GPs), the partitioned finite element method (PFEM) is combined with the Gp-dPHS method. By f…
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…
Variance based sensitivity analysis for Monte Carlo and importance sampling reliability assessment with Gaussian processes
Morgane Menz, Sylvain Dubreuil, Jérôme Morio +3
Running a reliability analysis on engineering problems involving complex numerical models can be computationally very expensive, requiring advanced simulation methods to reduce the…