activity
20132023
most citedOptimal Transport with Proximal Splitting

190 citations · 260 across the 16 of their papers we have counts for

collaborators

20 papers

math.NA2023

On the numerical approximation of Blaschke-Santaló diagrams using Centroidal Voronoi Tessellations

Beniamin Bogosel, Giuseppe Buttazzo, Edouard Oudet

Identifying Blaschke-Santaló diagrams is an important topic that essentially consists in determining the image of a map , where the dimension of the…

stat.ME2022★ 1 cited

The Fixed Landscape Inference MethOd (flimo): a versatile alternative to Approximate Bayesian Computation, faster by several orders of magnitude

Sylvain Moinard, Edouard Oudet, Didier Piau +2

Modelling in biology must adapt to increasingly complex and massive data. The efficiency of the inference algorithms used to estimate model parameters is therefore questioned. Many…

math.AP2022★ 4 cited

Maximization of Neumann eigenvalues

Dorin Bucur, Eloi Martinet, Edouard Oudet

This paper is motivated by the maximization of the -th eigenvalue of the Laplace operator with Neumann boundary conditions among domains of with prescribed measu…

math.OC2021

Longest minimal length partitions

Beniamin Bogosel, Edouard Oudet

This article provides numerical evidence that under volume constraint the ball is the set which maximizes the perimeter of the least-perimeter partition into cells with prescribed…

math.SP2020★ 3 cited

Computation of free boundary minimal surfaces via extremal Steklov eigenvalue problems

Chiu-Yen Kao, Braxton Osting, Èdouard Oudet

Recently Fraser and Schoen showed that the solution of a certain extremal Steklov eigenvalue problem on a compact surface with boundary can be used to generate a free boundary mini…

math.NA2020★ 1 cited

Numerical computation of the cut locus via a variational approximation of the distance function

François Générau, Édouard Oudet, Bozhidar Velichkov

We propose a new method for the numerical computation of the cut locus of a compact submanifold of without boundary. This method is based on a convex variational pro…