Deep Mercer Gaussian Process (DMGP) Regression

We provide the code used in our paper Faster Gaussian Processes via Deep Embeddings.

Prerequisites

TensorFlow version 2.1.0
TensorFlow Probability version 0.9.0
GPflow version 2.0.0 or newer

Source code

The following files can be found in the src directory :

• dmgp_model.py: implementation of the DMGP model
• helper.py: various utility gunctions
• hermite_coeff.npy: a numpy array containing the Hermite polynomial coefficients needed for the DMGP model
• main_realworld.py: code for replicating the results over the real-world datasets
• main_simulated_data.py: code for replicating the results over the two simulated datasets