ReactiveMP.jl: A Julia Package for Reactive Message Passing-based Bayesian Inference

Dmitry Bagaev (Corresponding author), Bert de Vries (Corresponding author)

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Abstract

ReactiveMP.jl is a native Julia implementation of reactive message passing-based Bayesian inference in probabilistic graphical models with Factor Graphs. The package does Constrained Bethe Free Energy minimisation and supports both exact and variational Bayesian inference, provides a convenient syntax for model specification and allows for extra factorisation and form constraints specification of the variational family of distributions. In addition, ReactiveMP.jl includes a large range of standard probabilistic models and can easily be extended to custom novel nodes and message update rules. In contrast to non-reactive (imperatively coded) Bayesian inference packages, ReactiveMP.jl scales easily to support inference on a standard laptop for large conjugate models with tens of thousands of variables and millions of nodes.
Original languageEnglish
Number of pages2
JournalJuliaCon Proceedings
Volume1
Issue number1
DOIs
Publication statusPublished - 29 Jan 2022

Keywords

  • Bayesian Inference,
  • Julia
  • Factor Graphs
  • Graphical Models
  • Free Energy Minimzation
  • Message Passing
  • Reactive Programming
  • variational inference

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