GPflow

A tutorial on Gaussian Process Regression for molecules using GPflow! @ryangriff123/gaussian-process-regression-on-molecules-in-gpflow-ee6fedab2130?source=friends_link&sk=224296dc6433c76c2cf8dfdee9305207" target="_blank" rel="nofollow noopener">medium.com/@ryangriff123/… @GPflowProject

Here is a visual of how samples from a Gaussian process update in light of new data. Made with @manim_community

Used GPflow before? Liked it? Didn't like it? We are running a survey to understand some of the challenges that people experience when using GPflow and where improvements could be made. Any answers you provide will help! Survey link: docs.google.com/forms/d/e/1FAI…

Our tutorial on sparse Gaussian processes (GPs) and variational inference (VI) is online: arxiv.org/abs/2012.13962 covering interdomain, multioutput and deep GPs, as well as importance-weighted VI, but also VI with neural networks! @vdutor @scien_ti_st @NicolasDurrande

What is Trieste? We recently launched our open-source toolbox: Trieste. It's a Python library for Bayesian optimization, based on @TensorFlow and @GPflowProject secondmind.ai/labs/trieste-o…