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List of probabilistic programming languages

From EverybodyWiki Bios & Wiki



List of probabilistic programming languages[edit]

Name Extends from Host language
Analytica[1] C++
bayesloop[2][3] Python Python
CuPPL[4] NOVA[5]
Venture[6] Scheme C++
Probabilistic-C[7] C C
Anglican[8] Clojure Clojure
IBAL[9] OCaml
BayesDB[10] SQLite, Python
PRISM[11] B-Prolog
Infer.NET[12] .NET Framework .NET Framework
dimple[13] MATLAB, Java
chimple[14] MATLAB, Java
BLOG[15] Java
delSAT[16] Answer set programming, SAT (DIMACS CNF)
PSQL[17] SQL
BUGS[18]
FACTORIE[19] Scala
PMTK[20] MATLAB MATLAB
Alchemy[21] C++
Dyna[22] Prolog
Figaro[23] Scala
Church[24] Scheme Various: JavaScript, Scheme
ProbLog[25] Prolog Python, Jython
ProBT[26] C++, Python
Stan[27] C++
Hakaru[28] Haskell Haskell
BAli-Phy (software)[29] Haskell C++
ProbCog[30] Java, Python
Gamble[31] Racket
PWhile[32] While Python
Tuffy[33] Java
PyMC3[34] Python, Theano Python
PyMC4[35] Python, TensorFlow Probability Python
greta[36] TensorFlow R
pomegranate[37] Python Python
Lea[38] Python Python
WebPPL[39] JavaScript JavaScript
Picture[40] Julia Julia
Turing.jl[41] Julia Julia
Gen[42] Julia Julia
Low-level First-order PPL[43] Python, Clojure, Pytorch Various: Python, Clojure
Troll[44] Moscow ML
Edward[45] TensorFlow Python
TensorFlow Probability[46] TensorFlow Python
Edward2[47] TensorFlow Probability Python
Pyro[48] PyTorch Python
Saul[49] Scala Scala
RankPL[50] Java
Birch[51] C++
PSI[52] D

Difficulty[edit]

Reasoning about variables as probability distributions causes difficulties for novice programmers, but these difficulties can be addressed through use of Bayesian network visualisations and graphs of variable distributions embedded within the source code editor.[53]

Notes[edit]

  1. ↑ "Analytica-- A Probabilistic Modeling Language". lumina.com.
  2. ↑ "bayesloop: Probabilistic programming framework that facilitates objective model selection for time-varying parameter models".
  3. ↑ "GitHub -- bayesloop".
  4. ↑ "Probabilistic Programming with CuPPL". popl19.sigplan.org.
  5. ↑ "NOVA: A Functional Language for Data Parallelism". acm.org.
  6. ↑ "Venture -- a general-purpose probabilistic programming platform". mit.edu.
  7. ↑ "Probabilistic C". ox.ac.uk.
  8. ↑ "The Anglican Probabilistic Programming System". ox.ac.uk.
  9. ↑ "IBAL Home Page". Archived from the original on December 26, 2010. Unknown parameter |url-status= ignored (help)
  10. ↑ "BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself". GitHub.
  11. ↑ "PRISM: PRogramming In Statistical Modeling". rjida.meijo-u.ac.jp.
  12. ↑ "Infer.NET". microsoft.com. Microsoft.
  13. ↑ "Dimple Home Page". analog.com.
  14. ↑ "Chimple Home Page". analog.com.
  15. ↑ "Bayesian Logic (BLOG)". mit.edu. Archived from the original on June 16, 2011. Unknown parameter |url-status= ignored (help)
  16. ↑ "delSAT (probabilistic SAT/ASP)".
  17. ↑ Dey, Debabrata; Sarkar, Sumit (1998). "PSQL: A query language for probabilistic relational data". Data & Knowledge Engineering. 28: 107–120. doi:10.1016/S0169-023X(98)00015-9.
  18. ↑ "The BUGS Project - MRC Biostatistics Unit". cam.ac.uk.
  19. ↑ "Factorie - Probabilistic programming with imperatively-defined factor graphs - Google Project Hosting". google.com.
  20. ↑ "PMTK3 - probabilistic modeling toolkit for Matlab/Octave, version 3 - Google Project Hosting". google.com.
  21. ↑ "Alchemy - Open Source AI". washington.edu.
  22. ↑ "Dyna". www.dyna.org.
  23. ↑ "Charles River Analytics - Probabilistic Modeling Services". cra.com.
  24. ↑ "Church". mit.edu.
  25. ↑ "ProbLog: Probabilistic Programming". dtai.cs.kuleuven.be.
  26. ↑ ProbaYes. "ProbaYes - Ensemble, nous valorisations vos données". probayes.com.
  27. ↑ "Stan". mc-stan.org.
  28. ↑ "Hakaru Home Page". hakaru-dev.github.io/.
  29. ↑ "BAli-Phy Home Page". bali-phy.org.
  30. ↑ "ProbCog". GitHub.
  31. ↑ Culpepper, Ryan (January 17, 2017). "gamble: Probabilistic Programming" – via GitHub.
  32. ↑ "PWhile Compiler". GitHub.
  33. ↑ "Tuffy: A Scalable Markov Logic Inference Engine". stanford.edu.
  34. ↑ PyMC devs. "PyMC3". pymc-devs.github.io.
  35. ↑ Developers, PyMC (2018-05-17). "Theano, TensorFlow and the Future of PyMC". PyMC Developers. Retrieved 2019-01-25.
  36. ↑ "greta: simple and scalable statistical modelling in R". GitHub. Retrieved 2018-10-02.
  37. ↑ "Home — pomegranate 0.10.0 documentation". pomegranate.readthedocs.io. Retrieved 2018-10-02.
  38. ↑ "Lea Home Page". bitbucket.org.
  39. ↑ "WebPPL Home Page". github.com/probmods/webppl.
  40. ↑ "Short probabilistic programming machine-learning code replaces complex programs for computer-vision tasks". KurzweilAI. April 13, 2015. Retrieved 27 Nov 2017.
  41. ↑ "The Turing language for probabilistic programming".
  42. ↑ "Gen: A General Purpose Probabilistic Programming Language with Programmable Inference". Retrieved 2019-06-17.
  43. ↑ "LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models". ox.ac.uk.
  44. ↑ "Troll dice roller and probability calculator".
  45. ↑ "Edward – Home". edwardlib.org. Retrieved 2017-01-17.
  46. ↑ TensorFlow (2018-04-11). "Introducing TensorFlow Probability". TensorFlow. Retrieved 2018-10-02.
  47. ↑ "'Edward2' TensorFlow Probability module". GitHub. Retrieved 2018-10-02.
  48. ↑ "Pyro". pyro.ai. Retrieved 2018-02-09.
  49. ↑ "CogComp - Home".
  50. ↑ Rienstra, Tjitze (2018-01-18), RankPL: A qualitative probabilistic programming language based on ranking theory, retrieved 2018-01-18
  51. ↑ "Probabilistic Programming in Birch". birch-lang.org. Retrieved 2018-04-20.
  52. ↑ "PSI Solver - Exact inference for probabilistic programs". psisolver.org. Retrieved 2019-08-18.
  53. ↑ Gorinova, Maria I.; Sarkar, Advait; Blackwell, Alan F.; Syme, Don (2016-01-01). A Live, Multiple-Representation Probabilistic Programming Environment for Novices. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. CHI '16. New York, NY, USA: ACM. pp. 2533–2537. doi:10.1145/2858036.2858221. ISBN 9781450333627. Search this book on


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