A painless GP implementation library for educational purpose.

Files explanation:
sgp.ipynb: Simple GP Implementation in an hour (GP tutorial-E02)
sgp_chs.ipynb: Simple GP Implementation in an hour in Chinese (GP tutorial-E02)

cigp_v10: conditional independent GP (cigp) for multivariate output.
cigp_dkl: CIGP with deep kernel learning (DKL), which pass the input X through a NN before reaching a normal GP.
cigp_v12: CIGP with a given mean function
cigp_v14: CIGP with a mixture of kernels

gpdm_v2: Gaussian Process Dynamical Model (Wang et al., 2005), which contains 2 GPs to handle dynamics and latent-to-observation mapping respectively. Version 2 contains a mixture of kernels.