Skip to content

vincentadam87/SVGPs

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

SVGPs

Sparse Variational (Coupled) Gaussian Processes

A variational treatment of inference and learning in models including multiple latent Gaussian Processes.

Key reference is

@misc{1711.01131,
Author = {Vincent Adam},
Title = {Structured Variational Inference for Coupled Gaussian Processes},
Year = {2017},
Eprint = {arXiv:1711.01131},
}

Requirements (Python 3)

  • tensorflow==1.1.0
  • numpy==1.12.1
  • matplotlib==2.0.2

The python implementation heavily relies on GPflow

About

Interacting Sparse Variational Gaussian Processes

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published