Fast Bayesian Inference with RxInfer.jl | Dmitry Bagaev | Julia User Group Munich
Автор: jolin․io
Загружено: 2024-07-15
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This is the recording of this meetup https://www.meetup.com/julia-user-gro... by the Julia User Group Munich.
https://rxinfer.ml/
A path to fast and scalable Bayesian inference (Dmitry Bagaev)
Given a probabilistic model, RxInfer allows for an efficient message-passing based Bayesian inference. It uses the model structure to generate an algorithm that consists of a sequence of local computations on a Forney-style factor graph (FFG) representation of the model. RxInfer.jl has been designed with a focus on efficiency, scalability and maximum performance for running inference with reactive message passing. It excels in models with conjugate likelihood-prior pairings. RxInfer also supports non-conjugate inference and is continually being improved to handle a broader class of models.
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![[09x10] Intro to RxInfer.jl | Automatic Bayesian Inference on Factor Graph with Message Passing](https://imager.clipsaver.ru/_vVHWzK9NEI/max.jpg)
![[09x11] Real-time, Streaming Bayesian Analysis using RxInfer.jl](https://imager.clipsaver.ru/mJkMCwugI1A/max.jpg)
