rhine-bayes: monad-bayes backend for Rhine

[ bsd3, frp, library, program ] [ Propose Tags ]

This package provides a backend to the `monad-bayes` library, enabling you to write stochastic processes as signal functions, and performing online machine learning on them.

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Versions [RSS]
Change log ChangeLog.md
Dependencies base (>=4.11 && <4.18), dunai (>=0.8), log-domain (>=0.12), mmorph, monad-bayes (>=1.1.0), rhine (==, rhine-bayes, rhine-gloss, time, transformers (>=0.5) [details]
License BSD-3-Clause
Author Manuel Bärenz
Maintainer programming@manuelbaerenz.de
Category FRP
Source repo head: git clone git@github.com:turion/rhine.git
this: git clone git@github.com:turion/rhine.git(tag v0.8.1.1)
Uploaded by turion at 2023-02-17T13:42:05Z
Distributions NixOS:
Executables rhine-bayes-gloss
Downloads 25 total (3 in the last 30 days)
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Status Docs available [build log]
Last success reported on 2023-02-17 [all 1 reports]

Readme for rhine-bayes-

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This package connects rhine to the monad-bayes library for probabilistic programming and inference. It provides:

  • Some standard stochastic processes such as Brownian Motion and LevĂ˝ processes
  • A particle filter inference method called Sequential Monte Carlo

This allows you to do interactive probabilistic (i.e. involving randomness) programs, and at the same time perform online inference, or realtime machine learning. An example for this is given in rhine-bayes/app/Main.hs, where inference is performed both on simulated values as well as external input given by the user.