arXiv stat.ML
· Papers
Covariance-Boosted Gaussian Processes for Spatiotemporal Irregularities
arXiv:2607.23018v1 Announce Type: new Abstract: Nonstationary Gaussian process (GP) models are powerful tools for capturing input-dependent variability by adapting to observed data. However, with limited sampling and highly parameterized covariance structure, they are often prone to overfitting and overconfident uncert