3 papers
stat.ML2026
Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
Aurélien Pion, Emmanuel Vazquez
Gaussian process (GP) predictive distributions are commonly used in Bayesian optimization (BO) to guide the selection of evaluation points for expensive objective functions. The ch…
stat.ML2025
Design-marginal calibration of Gaussian process predictive distributions: Bayesian and conformal approaches
Aurélien Pion, Emmanuel Vazquez
We study the calibration of Gaussian process (GP) predictive distributions in the interpolation setting from a design-marginal perspective. Conditioning on the data and averaging o…
cs.LG2024
Gaussian process interpolation with conformal prediction: methods and comparative analysis
Aurélien Pion, Emmanuel Vazquez
This article advocates the use of conformal prediction (CP) methods for Gaussian process (GP) interpolation to enhance the calibration of prediction intervals. We begin by illustra…