3 papers
math.ST2026
Gradient-enhanced global sensitivity analysis with Poincar{é} chaos expansions
O Roustant, N Lüthen, David Heredia +1
Spectral methods, also known as chaos expansions, are widely used in global sensitivity analysis (GSA), as they leverage orthogonal bases of L2 spaces to efficiently compute Sobol'…
physics.flu-dyn2026
Physics-informed, boundary-constrained Gaussian process regression for the reconstruction of fluid flow fields
Adrian Padilla-Segarra, Pascal Noble, Olivier Roustant +1
Gaussian process regression techniques have been used in fluid mechanics for the reconstruction of flow fields from a reduction-of-dimension perspective. A main ingredient in this…
stat.ML2026
Multifidelity Gaussian process regression for solving nonlinear partial differential equations
Fatima-Zahrae El-Boukkouri, Josselin Garnier, Olivier Roustant
Solving nonlinear partial differential equations (PDEs) using kernel methods offers a compelling alternative to traditional numerical solvers. However, the performance of these met…