https://github.com/ReactiveBayes/ReactiveMP.jl

High-performance reactive message-passing based Bayesian inference engine
https://github.com/ReactiveBayes/ReactiveMP.jl

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: about 1 month ago
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High-performance reactive message-passing based Bayesian inference engine

• Host: GitHub
• URL: https://github.com/ReactiveBayes/ReactiveMP.jl
• Owner: ReactiveBayes
• License: mit
• Created: 2019-12-23T15:02:58.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2024-04-12T15:01:44.000Z (8 months ago)
• Last Synced: 2024-04-13T00:49:46.804Z (8 months ago)
• Topics: bayesian-inference, inference, julia, message-passing, probabilistic-graphical-models, probabilistic-programming, variational-bayes, variational-inference
• Language: Julia
• Homepage:
• Size: 105 MB
• Stars: 89
• Watchers: 13
• Forks: 12
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

Awesome Lists containing this project

• awesome-sciml - biaslab/ReactiveMP.jl: Julia package for automatic Bayesian inference on a factor graph with reactive message passing

README

        
# ReactiveMP.jl

| **Documentation**                                                         | **Build Status**                 | **Coverage**                       | **Zenodo DOI**                   | **Pkg Eval**   |

|:-------------------------------------------------------------------------:|:--------------------------------:|:----------------------------------:|:--------------------------------:|:--------------:|

| [![][docs-stable-img]][docs-stable-url] [![][docs-dev-img]][docs-dev-url] | [![CI][ci-img]][ci-url]         | [![Codecov][codecov-img]][codecov-url] | [![DOI][zenodo-img]][zenodo-url] | [![PkgEval][pkgeval-img]][pkgeval-url] |

[docs-dev-img]: https://img.shields.io/badge/docs-dev-blue.svg

[docs-dev-url]: https://reactivebayes.github.io/ReactiveMP.jl/dev

[docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg

[docs-stable-url]: https://reactivebayes.github.io/ReactiveMP.jl/stable

[ci-img]: https://github.com/reactivebayes/ReactiveMP.jl/actions/workflows/ci.yml/badge.svg?branch=master

[ci-url]: https://github.com/reactivebayes/ReactiveMP.jl/actions

[codecov-img]: https://codecov.io/gh/reactivebayes/ReactiveMP.jl/branch/master/graph/badge.svg

[codecov-url]: https://codecov.io/gh/reactivebayes/ReactiveMP.jl?branch=master

[zenodo-img]: https://zenodo.org/badge/DOI/10.5281/zenodo.8381133.svg

[zenodo-url]: https://zenodo.org/doi/10.5281/zenodo.5913616

[pkgeval-img]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/R/ReactiveMP.svg

[pkgeval-url]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/R/ReactiveMP.html

# Reactive message passing engine

ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called [RxInfer](https://github.com/reactivebayes/RxInfer.jl). While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and dynamic datasets. 

## Examples and tutorials

The ReactiveMP.jl package is intended for advanced users with a deep understanding of message passing principles.

Accesible tutorials and examples are available in the [RxInfer documentation](https://reactivebayes.github.io/RxInfer.jl/stable/).

# License

MIT License Copyright (c) 2021-2024 BIASlab, 2024-present ReactiveBayes