# 概率编程

## 概率编程语言

### 关系

PRM的开发通常具有一组算法，用于关注的分布的归约、推理和发现，它们被嵌入到对应的PRPL中。

## 概率编程语言列表

[17] C++
bayesloop[18][19] Python Python
CuPPL[20] NOVA[21]
Venture[22] Scheme C++
Probabilistic-C[23] C C
Anglican[24] Clojure Clojure
IBAL[25] OCaml
BayesDB[26] SQLite, Python
PRISM[13] B-Prolog英语B-Prolog
Infer.NET英语Infer.NET[12] .NET框架 .NET框架
dimple[10] MATLAB, Java
chimple[11] MATLAB, Java
BLOG[27] Java
delSAT[28] 回答集编程, SAT (DIMACS CNF)
PSQL[29] SQL
BUGS[14]
FACTORIE[30] Scala Scala
PMTK[31] MATLAB MATLAB
Alchemy[32] C++
Dyna[33] Prolog
Figaro[34] Scala Scala
[35] Scheme 各种: JavaScript, Scheme
ProbLog[36] Prolog Python, Jython
ProBT[37] C++, Python
Stan英语Stan (software)[15] C++
ProbCog[40] Java, Python
Gamble[41] Racket
PWhile[42] While Python
Tuffy[43] Java
PyMC3[44] Python, Theano Python
PyMC4[45] Python, TensorFlow Probability Python
Rainier[46][47] Scala Scala
greta[48] TensorFlow R
pomegranate[49] Python Python
Lea[50] Python Python
WebPPL[51] JavaScript JavaScript
Let's Chance[52] Scratch JavaScript
Picture[4] Julia Julia
Turing.jl[53] Julia Julia
Gen[54] Julia Julia

Troll[56] Moscow ML
Edward[57] TensorFlow Python
TensorFlow Probability[58] TensorFlow Python
Edward2[59] TensorFlow Probability Python
Pyro[60] PyTorch Python
Saul[61] Scala Scala
Stan[62] C++, Python, R
RankPL[63] Java
Birch[64] C++
PSI[65] D

## 注释

1. ^ Probabilistic programming does in 50 lines of code what used to take thousands. phys.org. April 13, 2015 [2015-04-13]. （原始内容存档于2021-01-28）.
2. ^ Probabilistic Programming. probabilistic-programming.org. [December 24, 2013]. （原始内容存档于January 10, 2016）.
3. ^ Pfeffer, Avrom (2014), Practical Probabilistic Programming, Manning Publications. p.28. ISBN 978-1 6172-9233-0
4. Short probabilistic programming machine-learning code replaces complex programs for computer-vision tasks. KurzweilAI. April 13, 2015 [27 Nov 2017]. （原始内容存档于2021-02-12）.
5. ^ Hardesty, Larry. Graphics in reverse. April 13, 2015 [2021-01-16]. （原始内容存档于2021-01-22）.
6. ^ MIT shows off machine-learning script to make CREEPY HEADS. [2021-01-16]. （原始内容存档于2019-09-20）.
7. ^ MIT's Gen programming system flattens the learning curve for AI projects. VentureBeat. 2019-06-27 [2019-06-27]. （原始内容存档于2021-01-24） （美国英语）.
8. ^ Predicting Drug-Induced Liver Injury with Bayesian Machine Learning, 2019 [2021-01-16], （原始内容存档于2020-08-06）
9. ^ ∂P: A Differentiable Programming System to Bridge Machine Learning and Scientific Computing, 2019,
12. Infer.NET. microsoft.com. Microsoft. [2021-01-16]. （原始内容存档于2016-12-06）.
13. PRISM: PRogramming In Statistical Modeling. rjida.meijo-u.ac.jp. [July 8, 2015]. （原始内容存档于March 1, 2015）.
14. The BUGS Project - MRC Biostatistics Unit. cam.ac.uk. [January 12, 2011]. （原始内容存档于March 14, 2014）.
15. Stan. mc-stan.org. （原始内容存档于2012-09-03）.
16. ^ The Algorithms Behind Probabilistic Programming. [2017-03-10]. （原始内容存档于2021-01-29）.
17. ^ Analytica-- A Probabilistic Modeling Language. lumina.com. [2022-01-03]. （原始内容存档于2021-01-28）.
18. ^ bayesloop: Probabilistic programming framework that facilitates objective model selection for time-varying parameter models. [2021-01-16]. （原始内容存档于2020-12-01）.
19. ^ GitHub -- bayesloop. [2021-01-16]. （原始内容存档于2020-09-28）.
20. ^ Probabilistic Programming with CuPPL. popl19.sigplan.org. [2021-01-16]. （原始内容存档于2019-01-21）.
21. ^
22. ^ Venture -- a general-purpose probabilistic programming platform. mit.edu. [September 20, 2014]. （原始内容存档于January 25, 2016）.
23. ^ Probabilistic C. ox.ac.uk. [March 24, 2015]. （原始内容存档于January 4, 2016）.
24. ^ The Anglican Probabilistic Programming System. ox.ac.uk. [2021-01-16]. （原始内容存档于2020-10-26）.
26. ^ BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. GitHub. [2021-01-16]. （原始内容存档于2020-09-21）.
27. ^ Bayesian Logic (BLOG). mit.edu. （原始内容存档于June 16, 2011）.
28. ^ delSAT (probabilistic SAT/ASP). [2021-01-16]. （原始内容存档于2020-10-15）.
29. ^ Dey, Debabrata; Sarkar, Sumit. PSQL: A query language for probabilistic relational data. Data & Knowledge Engineering. 1998, 28: 107–120. doi:10.1016/S0169-023X(98)00015-9.
30. ^ Factorie - Probabilistic programming with imperatively-defined factor graphs - Google Project Hosting. google.com. [2021-01-16]. （原始内容存档于2012-04-14）.
31. ^ PMTK3 - probabilistic modeling toolkit for Matlab/Octave, version 3 - Google Project Hosting. google.com. [2021-01-16]. （原始内容存档于2011-04-10）.
32. ^ Alchemy - Open Source AI. washington.edu. [2021-01-16]. （原始内容存档于2008-06-16）.
33. ^ Dyna. www.dyna.org. [January 12, 2011]. （原始内容存档于January 17, 2016）.
34. ^
35. ^ Church. mit.edu. [April 8, 2013]. （原始内容存档于January 14, 2016）.
36. ^ ProbLog: Probabilistic Programming. dtai.cs.kuleuven.be. [2021-01-16]. （原始内容存档于2020-11-08）.
37. ^ ProbaYes. ProbaYes - Ensemble, nous valorisations vos données. probayes.com. [November 26, 2013]. （原始内容存档于March 5, 2016）.
40. ^ ProbCog. GitHub. [2021-01-16]. （原始内容存档于2020-11-29）.
41. ^ Culpepper, Ryan. gamble: Probabilistic Programming. January 17, 2017 [2021-01-16]. （原始内容存档于2020-11-06） –通过GitHub.
42. ^ PWhile Compiler. GitHub. [2021-01-16]. （原始内容存档于2020-10-17）.
43. ^ Tuffy: A Scalable Markov Logic Inference Engine. stanford.edu. [2021-01-16]. （原始内容存档于2020-07-22）.
44. ^ PyMC devs. PyMC3. pymc-devs.github.io. [2021-01-16]. （原始内容存档于2017-08-16）.
45. ^ Developers, PyMC. The Future of PyMC3, or: Theano is Dead, Long Live Theano. PyMC Developers. 2020-10-26 [2021-01-17]. （原始内容存档于2021-01-15）. PyMC4, which is based on TensorFlow, will not be developed further.
46. ^ stripe/rainier, Stripe, 2020-08-19 [2020-08-26], （原始内容存档于2021-02-19）
47. ^ Rainier · Bayesian inference for Scala. samplerainier.com. [2020-08-26].
48. ^ greta: simple and scalable statistical modelling in R. GitHub. [2018-10-02]. （原始内容存档于2018-10-03）.
49. ^ Home — pomegranate 0.10.0 documentation. pomegranate.readthedocs.io. [2018-10-02]. （原始内容存档于2021-01-22） （英语）.
52. ^ Let's Chance: Playful Probabilistic Programming for Children | Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. dl.acm.org. [2020-08-01]. doi:10.1145/3334480.3383071. （原始内容存档于2021-01-22） （英语）.
53. ^
54. ^ Gen: A General Purpose Probabilistic Programming Language with Programmable Inference. [2019-06-17]. （原始内容存档于2020-11-12）.
55. ^
56. ^ Troll dice roller and probability calculator. [2021-01-16]. （原始内容存档于2021-01-25）.
57. ^ Edward – Home. edwardlib.org. [2017-01-17]. （原始内容存档于2020-11-08）.
58. ^ TensorFlow. Introducing TensorFlow Probability. TensorFlow. 2018-04-11 [2018-10-02]. （原始内容存档于2021-01-22）.
59. ^ 'Edward2' TensorFlow Probability module. GitHub. [2018-10-02]. （原始内容存档于2020-01-08） （英语）.
60. ^ Pyro. pyro.ai. [2018-02-09]. （原始内容存档于2021-01-19） （英语）.
61. ^ CogComp - Home. [2021-01-16]. （原始内容存档于2018-01-16）.
62. ^ Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation.. [2021-01-16]. （原始内容存档于2021-04-02）.
63. ^ Rienstra, Tjitze, RankPL: A qualitative probabilistic programming language based on ranking theory, 2018-01-18 [2018-01-18], （原始内容存档于2020-11-09）
64. ^ Probabilistic Programming in Birch. birch-lang.org. [2018-04-20]. （原始内容存档于2021-01-29）.
65. ^ PSI Solver - Exact inference for probabilistic programs. psisolver.org. [2019-08-18]. （原始内容存档于2021-01-23）.
66. ^ Gorinova, Maria I.; Sarkar, Advait; Blackwell, Alan F.; Syme, Don. A Live, Multiple-Representation Probabilistic Programming Environment for Novices. CHI '16. New York, NY, USA: ACM. 2016-01-01: 2533–2537. ISBN 9781450333627. doi:10.1145/2858036.2858221. `|journal=`被忽略 (帮助)