GPflow (@GPflowProject) header
GPflow (@GPflowProject) profile picture

GPflow

@GPflowProject

Gaussian Processes in TensorFlow! site: https://xitter.gq/t.co/D4vly0ASH5 gh: https://xitter.gq/t.co/8SVShaZ9Ez

 Bayesian Paradise
Joined July 2020
  • Tweets5
  • Following22
  • Followers109
A tutorial on Gaussian Process Regression for molecules using GPflow! medium.com/@ryangriff123/gau… @GPflowProject
Image from Ryan-Rhys Griffiths (@Ryan__Rhys)
4
32
5
200
Here is a visual of how samples from a Gaussian process update in light of new data. Made with @manim_community
4
31
4
260
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/1F…
GPflow survey

GPflow survey

We would like to understand some of the challenges that people experience when using GPflow and where improvements could be made. Any answers you provide will help! We would like to collect responses...

docs.google.com
2
1
9
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
A Tutorial on Sparse Gaussian Processes and Variational Inference

A Tutorial on Sparse Gaussian Processes and Variational Inference

Gaussian processes (GPs) provide a framework for Bayesian inference that can offer principled uncertainty estimates for a large range of problems. For example, if we consider regression problems...

arxiv.org
3
13
1
83
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…
1
4
2
14
Load more