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ReactiveMP.jl

Julia package for reactive message passing Bayesian inference engine on a factor graph.

Note

This package exports only an inference engine, for the full ecosystem with convenient model and constraints specification we refer user to the RxInfer.jl package and its documentation.

Ideas and principles behind ReactiveMP.jl

ReactiveMP.jl is a particular implementation of message passing on factor graphs, which does not create any specific message passing schedule in advance, but rather reacts on changes in the data source (hence reactive in the name of the package). The detailed explanation of the ideas and principles behind the Reactive Message Passing can be found in PhD disseration of Dmitry Bagaev titled Reactive Probabilistic Programming for Scalable Bayesian Inference (link2, link3).

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.

Table of Contents

Index