Feature Space Adaptation for Effortless Gaussian Process Flows
FeatureFlow conditions Gaussian Processes on complex statements by operating in a finite-feature GP weight space instead of function values. This decouples sampling cost from resolution, allowing for practical hyperparameter optimization and enabling scalable flows for non-linear conditioning tasks like probabilistic downscaling.