Skip to content

astrowq/Celeste.jl

BranchesTags
 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2,314 Commits
benchmark
benchmark
 
 
bin
bin
 
 
cfg
cfg
 
 
contrib
contrib
 
 
deps
deps
 
 
doc
doc
 
 
experiments
experiments
 
 
src
src
 
 
test
test
 
 
.gitignore
.gitignore
 
 
.travis.yml
.travis.yml
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
REQUIRE
REQUIRE
 
 

Repository files navigation

Celeste.jl

Build Status codecov.io

Celeste.jl finds and characterizes stars and galaxies in astronomical images. It performs approximate Bayesian inference as described in

Jeffrey Regier, Andrew Miller, David Schlegel, Ryan Adams, Jon McAuliffe, and Prabhat. "Approximate inference for constructing astronomical catalogs from images." In submission.

and

Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin Thomas, and Prabhat. “Cataloging the visible universe through Bayesian inference at petascale.” In: International Parallel and Distributed Processing Symposium (IPDPS), 2018.

and

Jeffrey Regier, Andrew Miller, Jon McAuliffe, Ryan Adams, Matt Hoffman, Dustin Lang, David Schlegel, and Prabhat. “Celeste: Variational inference for a generative model of astronomical images.” In: Proceedings of the 32nd International Conference on Machine Learning (ICML). 2015.

Please see the project wiki for documentation.

License

Celeste.jl is free software, licensed under the MIT "Expat" License.

About

Scalable inference for a generative model of astronomical images

Resources

Readme

License

MIT license
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

6 tags

Packages

No packages published

Languages

  • Jupyter Notebook 82.3%
  • Julia 15.5%
  • Python 1.8%
  • Other 0.4%