Gaussian process interpolation with conformal prediction: methods and comparative analysis

Autor: Pion, Aurélien, Vazquez, Emmanuel

Publikováno v: LOD 2024, 10th International Conference on Machine Learning, Optimization, and Data Science, Sep 2024, Castiglione della Pescaia Grosseto Italy, Italy

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 illustrating that using a GP model with parameters selected by maximum likelih

Externí odkaz: http://arxiv.org/abs/2407.08271