Skip to content

Latest commit

 

History

History
6 lines (6 loc) · 502 Bytes

README.md

File metadata and controls

6 lines (6 loc) · 502 Bytes

KAUST_GP

The code is for the 2023 KAUST competition. I construct a variational Gaussian Process regression model to predict the confidence intervals of the unknown parameters for the Matern covariance function. In addition, the model can provide the prediction intervals for the given large spatial datasets.

install GPyTorch pakage

conda install -c conda-forge gpytorch

How to check the code

all code details are in index.ipynb.