Predictive posterior sampling from non-stationnary Gaussian process priors via Diffusion models with application to climate data

Gabriel V Cardoso, Mike Pereira

Bayesian models based on Gaussian processes (GPs) offer a flexible framework to predict spatially distributed variables with uncertainty. But the use of nonstationary priors, often…