https://github.com/turinglang/bijectors.jl

Implementation of normalising flows and constrained random variable transformations
https://github.com/turinglang/bijectors.jl

bayesian-inference hacktoberfest mcmc-sampler transforms turing-language

Last synced: 4 months ago
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Implementation of normalising flows and constrained random variable transformations

• Host: GitHub
• URL: https://github.com/turinglang/bijectors.jl
• Owner: TuringLang
• License: mit
• Created: 2018-09-13T16:01:43.000Z (almost 7 years ago)
• Default Branch: main
• Last Pushed: 2025-03-10T18:03:13.000Z (4 months ago)
• Last Synced: 2025-03-10T19:22:36.510Z (4 months ago)
• Topics: bayesian-inference, hacktoberfest, mcmc-sampler, transforms, turing-language
• Language: Julia
• Homepage: https://turinglang.org/Bijectors.jl/
• Size: 911 KB
• Stars: 231
• Watchers: 15
• Forks: 35
• Open Issues: 51
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Bijectors.jl

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://turinglang.github.io/Bijectors.jl/stable)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://turinglang.github.io/Bijectors.jl/dev)

[![Interface tests](https://github.com/TuringLang/Bijectors.jl/workflows/Interface%20tests/badge.svg?branch=main)](https://github.com/TuringLang/Bijectors.jl/actions?query=workflow%3A%22Interface+tests%22+branch%3Amain)

[![AD tests](https://github.com/TuringLang/Bijectors.jl/workflows/AD%20tests/badge.svg?branch=main)](https://github.com/TuringLang/Bijectors.jl/actions?query=workflow%3A%22AD+tests%22+branch%3Amain)

*A package for transforming distributions, used by [Turing.jl](https://github.com/TuringLang/Turing.jl).*

Bijectors.jl implements both an interface for transforming distributions from Distributions.jl and many transformations needed in this context. This package is used heavily in the probabilistic programing language Turing.jl.

See the [documentation](https://turinglang.github.io/Bijectors.jl) for more.

## Do you want to contribute?

If you feel you have some relevant skills and are interested in contributing, please get in touch! You can find us in the #turing channel on the [Julia Slack](https://julialang.org/slack/) or [Discourse](discourse.julialang.org). If you're having any problems, please open a Github issue, even if the problem seems small (like help figuring out an error message). Every issue you open helps us to improve the library!