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https://github.com/probcomp/Gen.jl
A general-purpose probabilistic programming system with programmable inference
https://github.com/probcomp/Gen.jl
bayesian computer-vision deep-learning differentiable-programming gen julia-language machine-learning probabilistic-programming robotics
Last synced: 12 days ago
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A general-purpose probabilistic programming system with programmable inference
- Host: GitHub
- URL: https://github.com/probcomp/Gen.jl
- Owner: probcomp
- License: apache-2.0
- Created: 2018-08-21T21:42:42.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-05-01T06:33:56.000Z (6 months ago)
- Last Synced: 2024-05-02T00:28:48.145Z (6 months ago)
- Topics: bayesian, computer-vision, deep-learning, differentiable-programming, gen, julia-language, machine-learning, probabilistic-programming, robotics
- Language: Julia
- Homepage: https://gen.dev
- Size: 23.8 MB
- Stars: 1,770
- Watchers: 76
- Forks: 159
- Open Issues: 166
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Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- awesome-sciml - probcomp/Gen.jl: A general-purpose probabilistic programming system with programmable inference
README
# Gen.jl
[![Build Status](https://github.com/probcomp/Gen/workflows/ContinuousIntegration/badge.svg)](https://github.com/probcomp/Gen/actions)
[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://probcomp.github.io/Gen.jl/docs/stable)
[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://probcomp.github.io/Gen.jl/docs/dev)Gen: A General-Purpose Probabilistic Programming System with Programmable Inference
*Warning: This is rapidly evolving research software.*
See [https://gen.dev](https://gen.dev/) for introduction, documentation, and tutorials.
Gen was created at the [MIT Probabilistic Computing Project](http://probcomp.csail.mit.edu/). To get in contact, please email [email protected].
If you use Gen in your research, please cite our 2019 PLDI paper:
Gen: A General-Purpose Probabilistic Programming System with Programmable Inference. Cusumano-Towner, M. F.; Saad, F. A.; Lew, A.; and Mansinghka, V. K.
In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI ‘19). ([pdf](https://dl.acm.org/doi/10.1145/3314221.3314642)) ([bibtex](https://www.gen.dev/assets/gen-pldi.txt))