Guang Lin

A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling

Gaussian process (GP) modeling is widely used in computational science and engineering. However, fitting a GP to high-dimensional inputs remains challenging due to the curse of dimensionality. While various methods have been proposed to reduce input dimensionality, they typically follow a two-stage approach, performing...