2 papers
stat.ML2024
Posterior Covariance Structures in Gaussian Processes
Difeng Cai, Edmond Chow, Yuanzhe Xi
In this paper, we present a comprehensive analysis of the posterior covariance field in Gaussian processes, with applications to the posterior covariance matrix. The analysis is ba…
cs.LG2024
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling
Shifan Zhao, Jiaying Lu, Ji Yang +2
Gaussian Process Regression (GPR) is widely used in statistics and machine learning for prediction tasks requiring uncertainty measures. Its efficacy depends on the appropriate spe…