2 papers
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…
physics.flu-dyn2026
Divergence-Free Diffusion Models for Incompressible Fluid Flows
Wilfried Genuist, Ãric Savin, Filippo Gatti +1
Generative diffusion models are extensively used in unsupervised and self-supervised machine learning with the aim to generate new samples from a probability distribution estimated…