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tweag/monad-bayes: A library for probabilistic programming in Haskell.

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

tweag/monad-bayes

开源软件地址(OpenSource Url):

https://github.com/tweag/monad-bayes

开源编程语言(OpenSource Language):

Jupyter Notebook 94.4%

开源软件介绍(OpenSource Introduction):

monad-bayes

A library for probabilistic programming in Haskell. The emphasis is on composition of inference algorithms, and is implemented in terms of monad transformers.

See the documentation for a quick-start user guide and a reference overview of how it all works.

Created by Adam Scibior (@adscib), documentation by Reuben, maintained by Tweag I/O.

Project status

Now that monad-bayes has been released on Hackage, we will focus on improving documentation, adding a variety of applications, improving the API, and making inference more easily customizable.

Background

The basis for the code in this repository is the ICFP 2018 paper [2]. For the code associated with the Haskell2015 paper [1], see the haskell2015 tag.

[1] Adam M. Ścibior, Zoubin Ghahramani, and Andrew D. Gordon. 2015. Practical probabilistic programming with monads. In Proceedings of the 2015 ACM SIGPLAN Symposium on Haskell (Haskell ’15), Association for Computing Machinery, Vancouver, BC, Canada, 165–176.

[2] Adam M. Ścibior, Ohad Kammar, and Zoubin Ghahramani. 2018. Functional programming for modular Bayesian inference. In Proceedings of the ACM on Programming Languages Volume 2, ICFP (July 2018), 83:1–83:29.

[3] Adam M. Ścibior. 2019. Formally justified and modular Bayesian inference for probabilistic programs. Thesis. University of Cambridge.

Hacking

  1. Install stack by following these instructions.

  2. Clone the repository using one of these URLs:

    git clone [email protected]:tweag/monad-bayes.git
    git clone https://github.com/tweag/monad-bayes.git
    

Now you can use stack build, stack test and stack ghci.




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