This library contains code to fit Gaussian processes (GPs) using variational inference. The key reference is:
Hensman, James, Alexander Matthews, and Zoubin Ghahramani. "Scalable variational Gaussian process classification." (2015). Available here: http://proceedings.mlr.press/v38/hensman15.pdf
The code provides a simple implementation in Tensorflow 2. We also extend the methodology to do approximate variational inference in hierarchical multi-output Gaussian processes (MOGPs).