RxInfer.jl

Reactive Message Passing on Factor Graphs

Bayesian Inference at Scale

RxInfer.jl is a powerful Julia package built by the ReactiveBayes ecosystem, specifically designed to automate Bayesian inference using reactive message passing on constraint-based factor graphs.

Within the context of Active Inference, RxInfer allows practitioners to define models via readable Julia macros (powered by GraphPPL.jl), which compile into high-performance message passing networks (powered by ReactiveMP.jl and Rocket.jl).

This hybrid inference engine processes real-time streaming data, enabling seamless simulations of decision-making tasks, multi-agent scenarios, and generative world-models adapting to changing environments.

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Institute Repositories

Our GitHub organisation hosts extensive open-source simulation code, documentation infrastructure, and the web components you see here.

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