activity
20112023
most citedLearning "best" kernels from data in Gaussian process regression. With application to aerodynamics

27 citations · 34 across the 7 of their papers we have counts for

collaborators

8 papers

math-ph2023

Wigner measures of electromagnetic waves in heterogeneous bianisotropic media

Jean-Luc Akian, Éric Savin

We study the propagation of high-frequency electromagnetic waves in randomly heterogeneous bianisotropic media with dissipative properties. For that purpose we consider randomly fl…

math.AP2022

Well-posedness of a time-harmonic elasticity problem in a half-strip

Jean-Luc Akian

In this paper we establish that the time-harmonic elasticity problem in a half-strip with non-homogeneous Dirichlet conditions on its boundary section and traction-free conditions…

stat.ML2022★ 27 cited

Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics

Jean-Luc Akian, Luc Bonnet, Houman Owhadi +1

This paper introduces algorithms to select/design kernels in Gaussian process regression/kriging surrogate modeling techniques. We adopt the setting of kernel method solutions in a…

math-ph2021

A proof of the completeness of Lamb modes

Jean-Luc Akian

The aim of this paper is to give a precise proof of the completeness of Lamb modes and associated modes. This proof is relatively simple and short but relies on two powerful mathem…

math-ph2020

A proof of the convexity of the set of lamination parameters

Jean-Luc Akian

In this paper we show that the proof of the convexity of the set of lamination parameters given by J.L. Grenestedt and P. Gudmundson, which is extensively cited in the literature,…

math.NA2020★ 3 cited

Adaptive reconstruction of imperfectly-observed monotone functions, with applications to uncertainty quantification

L. Bonnet, J. -L. Akian, É. Savin +1

Motivated by the desire to numerically calculate rigorous upper and lower bounds on deviation probabilities over large classes of probability distributions, we present an adaptive…