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cs.LG2025
HiGP: A high-performance Python package for Gaussian Process
Hua Huang, Tianshi Xu, Yuanzhe Xi +1
Gaussian Processes (GPs) are flexible, nonparametric Bayesian models widely used for regression and classification because of their ability to capture complex data patterns and qua…
cs.LG2024★ 1 cited
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…