Hi, I’ve been using Turing.jl for various purposes, and recently I thought it might be easy to mimick inference from a basic discrete bayesian network like I could do with BayesNets.jl like this for example: bn = DiscreteBayesNet() push!( bn, DiscreteCPD( :a, # our root node …

Welcome to the forum! This is an interesting question, I’ve been thinking about a similar thing. Could you share your attempts?

Most contemporary PPLs are developed with continuous variables in mind. Therefore, for pure Bayesian networks, it’s best to use frameworks specialized to those.

Are there any Discrete Bayesian network frameworks in Julia?

I think so? A quick google search revaled BayesNets.jl . I am sure there is more, but I am more of a general PPL man myself, so not much experience with Bayesian networks.

How to mimick a Discrete Bayes Net in Turing.jl?

Specific Domains Probabilistic Programming

eteppo September 23, 2025, 1:16pm 6

Also see the RxInfer.jl tutorial on Bayesian networks.

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How to mimick a Discrete Bayes Net in Turing.jl?

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