RxInfer.jl

Free#57 of 106 in Statistical Analysis Software

RxInfer.jl: A focused Julia library for exact and variational inference on factor graphs. Ranked #57 of 106 in Statistical Analysis Software by our editors (3.7/10); pricing: Free plan; best for probabilistic inference in Julia.

3.7/10★★☆☆☆Editor score

Visit RxInfer.jl

At a glance

• Editor score
  3.7 / 10
• Pricing
  Free plan
• Best for
  Probabilistic inference in Julia
• Free plan
  Yes
• Paid from
  Free
• Deployment
  Desktop
• Facts checked
  24 Sep 2026

• Where it wins

  • Generates message-passing algorithms from factor graph structure
  • Supports exact belief propagation and variational message passing
  • Runs inference on static datasets and asynchronous data streams

• Where it doesn't

  • Focused on probabilistic inference rather than general statistics
  • Requires working in Julia and expressing models in its syntax
  • Customizing factor nodes and update rules calls for developer effort

Our verdict on RxInfer.jl

RxInfer.jl is an open-source Julia package for specifying probabilistic models and performing Bayesian inference on factor graphs. It is aimed at researchers and developers working with probabilistic models, machine learning, signal processing, and dynamic systems. Its focused scope suits people who want to define models in Julia and work with inferred posterior distributions, rather than those seeking a general-purpose statistical analysis environment.

A central capability is generating message-passing algorithms automatically from a model's factor graph structure. RxInfer.jl supports exact belief propagation and variational message passing, as well as hybrid models with discrete and continuous latent variables. Results include posterior marginals and predictions, with optional Bethe Free Energy reporting. Users who need a particular model component can define custom factor nodes and message update rules. This makes the package relevant to specialized inference workflows, though users should expect to work directly with probabilistic models and inference concepts.

Inference can run on static datasets or asynchronous data streams, which gives the package a fit for both fixed observations and streaming workflows. It is installed through Julia's package manager, runs on Linux, macOS, and Windows, and lists Python as an integration. The MIT-licensed package is self-hosted, with documentation and community support channels. Choose RxInfer.jl if your work is centered on Bayesian inference in Julia and its message-passing approach; consider a broader statistics tool if you need general-purpose analysis beyond probabilistic models.

Your product? Our editors can test RxInfer.jl in depth and publish a review, labelled as paid · from $149/mo →

RxInfer.jl pricing

RxInfer.jl fact sheet

RxInfer.jl integrations

RxInfer.jl lists 1 integrations on its own site.

• Python

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Last updated 7 Oct 2026 · How we research and update