layout: home
hero: name: EnhancedBayesianNetworks.jl text: Bayesian networks with continuous, functional, and imprecise nodes tagline: Build enhanced Bayesian networks, reduce them through structural reliability analysis, and query them with exact or credal inference. actions: - theme: brand text: Getting Started link: /manual/gettingstarted - theme: alt text: Introduction link: /manual/introduction - theme: alt text: View on GitHub link: https://github.com/JuliaUQ/EnhancedBayesianNetworks.jl
features:
title: Enhanced Bayesian networks details: Mix discrete, continuous, and functional nodes in a single model, with precise or imprecise (interval / probability-box) quantities.
title: Reduction & reliability details: Reduce an enhanced network to a Bayesian or credal network, evaluating functional nodes as structural reliability problems through UncertaintyQuantification.jl.
title: Exact & credal inference details: Variable elimination on Bayesian networks and lower/upper bounds on credal networks, alongside parameter learning and network plotting.
authors:
name: Andrea Perin platform: github link: https://github.com/andreaperin
name: Jasper Behrensdorf platform: github link: https://github.com/FriesischScott
name: Matteo Broggi platform: github link: https://github.com/teobros
name: Laurenz Knipper platform: github link: https://github.com/sitoryu
EnhancedBayesianNetworks.jl extends the classical Bayesian-network formalism with the continuous and functional nodes of structural reliability analysis, and with imprecision at every level. New here? Start with the Introduction for the concepts, or jump to Getting Started to install the package and run your first model.