Science Score: 59.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 6 DOI reference(s) in README -
✓Academic publication links
Links to: scholar.google -
✓Committers with academic emails
14 of 103 committers (13.6%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (16.5%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Bayesian inference with probabilistic programming.
Basic Info
- Host: GitHub
- Owner: TuringLang
- License: mit
- Language: Julia
- Default Branch: main
- Homepage: https://turinglang.org
- Size: 39.5 MB
Statistics
- Stars: 2,160
- Watchers: 50
- Forks: 228
- Open Issues: 88
- Releases: 213
Topics
Metadata Files
README.md
Turing.jl
Probabilistic programming and Bayesian inference in Julia
🚀 Get started
Install Julia (see the official Julia website; you will need at least Julia 1.10 for the latest version of Turing.jl). Then, launch a Julia REPL and run:
julia
julia> using Pkg; Pkg.add("Turing")
You can define models using the @model macro, and then perform Markov chain Monte Carlo sampling using the sample function:
```julia julia> using Turing
julia> @model function myfirstmodel(data) mean ~ Normal(0, 1) sd ~ truncated(Cauchy(0, 3); lower=0) data ~ Normal(mean, sd) end
julia> model = myfirstmodel(randn())
julia> chain = sample(model, NUTS(), 1000) ```
You can find the main TuringLang documentation at https://turinglang.org, which contains general information about Turing.jl's features, as well as a variety of tutorials with examples of Turing.jl models.
API documentation for Turing.jl is specifically available at https://turinglang.org/Turing.jl/stable.
🛠️ Contributing
Issues
If you find any bugs or unintuitive behaviour when using Turing.jl, please do open an issue! Please don't worry about finding the correct repository for the issue; we can migrate the issue to the appropriate repository if we need to.
Pull requests
We are of course also very happy to receive pull requests. If you are unsure about whether a particular feature would be welcome, you can open an issue for discussion first.
When opening a PR, non-breaking releases (patch versions) should target the main branch.
Breaking releases (minor version) should target the breaking branch.
If you have not received any feedback on an issue or PR for a while, please feel free to ping @TuringLang/maintainers in a comment.
💬 Other channels
The Turing.jl userbase tends to be most active on the #turing channel of Julia Slack.
If you do not have an invitation to Julia's Slack, you can get one from the official Julia website.
There are also often threads on Julia Discourse (you can search using, e.g., the turing tag).
🔄 What's changed recently?
We publish a fortnightly newsletter summarising recent updates in the TuringLang ecosystem, which you can view on our website, GitHub, or Julia Slack.
For Turing.jl specifically, you can see a full changelog in HISTORY.md or our GitHub releases.
🧩 Where does Turing.jl sit in the TuringLang ecosystem?
Turing.jl is the main entry point for users, and seeks to provide a unified, convenient interface to all of the functionality in the TuringLang (and broader Julia) ecosystem.
In particular, it takes the ability to specify probabilistic models with DynamicPPL.jl, and combines it with a number of inference algorithms, such as:
- Markov Chain Monte Carlo (both an abstract interface: AbstractMCMC.jl, and individual samplers, such as AdvancedMH.jl, AdvancedHMC.jl, and more).
- Variational inference using AdvancedVI.jl.
- Maximum likelihood and maximum a posteriori estimation, which rely on SciML's Optimization.jl interface.
Citing Turing.jl
If you have used Turing.jl in your work, we would be very grateful if you could cite the following:
Turing.jl: a general-purpose probabilistic programming language
Tor Erlend Fjelde, Kai Xu, David Widmann, Mohamed Tarek, Cameron Pfiffer, Martin Trapp, Seth D. Axen, Xianda Sun, Markus Hauru, Penelope Yong, Will Tebbutt, Zoubin Ghahramani, Hong Ge
ACM Transactions on Probabilistic Machine Learning, 2025 (Just Accepted)
Turing: A Language for Flexible Probabilistic Inference
Hong Ge, Kai Xu, Zoubin Ghahramani
Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1682-1690, 2018.
Expand for BibTeX
```bibtex @article{10.1145/3711897, author = {Fjelde, Tor Erlend and Xu, Kai and Widmann, David and Tarek, Mohamed and Pfiffer, Cameron and Trapp, Martin and Axen, Seth D. and Sun, Xianda and Hauru, Markus and Yong, Penelope and Tebbutt, Will and Ghahramani, Zoubin and Ge, Hong}, title = {Turing.jl: a general-purpose probabilistic programming language}, year = {2025}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3711897}, doi = {10.1145/3711897}, note = {Just Accepted}, journal = {ACM Trans. Probab. Mach. Learn.}, month = feb, } @InProceedings{pmlr-v84-ge18b, title = {Turing: A Language for Flexible Probabilistic Inference}, author = {Ge, Hong and Xu, Kai and Ghahramani, Zoubin}, booktitle = {Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics}, pages = {1682--1690}, year = {2018}, editor = {Storkey, Amos and Perez-Cruz, Fernando}, volume = {84}, series = {Proceedings of Machine Learning Research}, month = {09--11 Apr}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v84/ge18b/ge18b.pdf}, url = {https://proceedings.mlr.press/v84/ge18b.html}, } ```You can see the full list of publications that have cited Turing.jl on Google Scholar.
Owner
- Name: The Turing Language
- Login: TuringLang
- Kind: organization
- Website: http://turinglang.org
- Repositories: 28
- Profile: https://github.com/TuringLang
Bayesian inference with probabilistic programming
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Kai Xu | x****0@g****m | 1,203 |
| Hong Ge | h****4@c****k | 469 |
| Hong Ge | h****e@d****k | 286 |
| Cameron Pfiffer | c****r@g****m | 239 |
| David Widmann | d****n | 164 |
| Tor Erlend Fjelde | t****5@g****m | 97 |
| Martin Trapp | t****n@g****m | 93 |
| Mohamed Tarek | m****8@g****m | 79 |
| Emile Mathieu | e****u@s****k | 69 |
| github-actions[bot] | 4****] | 56 |
| Markus Hauru | m****s@m****g | 29 |
| Penelope Yong | p****m@g****m | 27 |
| Will Tebbutt | w****1@m****k | 25 |
| Adam Scibior | a****b@g****m | 22 |
| ZHUO QL | K****2 | 21 |
| Hessam Mehr | h****r@g****m | 13 |
| Xianda Sun | 5****3 | 13 |
| Emile Mathieu | e****m@b****r | 10 |
| Emma Smith | e****x@g****m | 9 |
| Ubuntu | u****u@i****l | 8 |
| Mohamed | m****y@y****m | 7 |
| Philipp Gabler | p****r | 6 |
| Harrison Wilde | h****e@o****m | 5 |
| Jaime RZ | j****3@g****m | 5 |
| Rik Huijzer | t****r@r****l | 5 |
| keorn | p****n@g****m | 3 |
| Arthur Lui | l****r@g****m | 3 |
| FredericWantiez | f****z@g****m | 3 |
| Pietro Monticone | 3****e | 3 |
| Tom Röschinger | 5****h | 3 |
| and 73 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 343
- Total pull requests: 525
- Average time to close issues: 9 months
- Average time to close pull requests: 24 days
- Total issue authors: 141
- Total pull request authors: 37
- Average comments per issue: 3.95
- Average comments per pull request: 3.59
- Merged pull requests: 290
- Bot issues: 0
- Bot pull requests: 194
Past Year
- Issues: 136
- Pull requests: 252
- Average time to close issues: about 2 months
- Average time to close pull requests: 14 days
- Issue authors: 40
- Pull request authors: 16
- Average comments per issue: 2.32
- Average comments per pull request: 2.89
- Merged pull requests: 120
- Bot issues: 0
- Bot pull requests: 97
Top Authors
Issue Authors
- penelopeysm (51)
- mhauru (33)
- torfjelde (28)
- yebai (23)
- DominiqueMakowski (11)
- ElOceanografo (7)
- tiemvanderdeure (6)
- astro-kevin (6)
- simonsteiger (6)
- PTWaade (5)
- SamuelBrand1 (4)
- willtebbutt (4)
- sunxd3 (4)
- CMoebus (3)
- itsdfish (3)
Pull Request Authors
- github-actions[bot] (237)
- penelopeysm (112)
- mhauru (70)
- torfjelde (55)
- yebai (33)
- devmotion (22)
- sunxd3 (16)
- JaimeRZP (12)
- Red-Portal (5)
- ElOceanografo (4)
- willtebbutt (4)
- AoifeHughes (3)
- FredericWantiez (3)
- shravanngoswamii (3)
- itsdfish (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- julia 1,087 total
- Total dependent packages: 25
- Total dependent repositories: 0
- Total versions: 204
juliahub.com: Turing
Bayesian inference with probabilistic programming.
- Homepage: https://turinglang.org
- Documentation: https://docs.juliahub.com/General/Turing/stable/
- License: MIT
-
Latest release: 0.40.2
published 7 months ago
Rankings
Dependencies
- actions/cache v1 composite
- actions/checkout v2 composite
- julia-actions/julia-buildpkg latest composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia v1 composite
- actions/cache v1 composite
- actions/checkout v2 composite
- julia-actions/julia-buildpkg latest composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia v1 composite
- JuliaRegistries/TagBot v1 composite
- actions/cache v1 composite
- actions/checkout v2 composite
- codecov/codecov-action v1 composite
- coverallsapp/github-action master composite
- julia-actions/julia-buildpkg latest composite
- julia-actions/julia-processcoverage v1 composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia v1 composite