LazyPPL: Laziness and Types in Non-Parametric Probabilistic Programs

Abstract

We introduce LazyPPL, a prototype probabilistic programming library for Haskell. The library emphasises the clarifying power of types, and the connection between non-parametric, stochastic processes and lazy (call by need) evaluation. We illustrate the power of the language with natural specifications of infinite structures including Poisson point processes, Gaussian processes, and Dirichlet Process clustering.

PDF NeurIPSW OpenReview Semantic Scholar

Cite

Text

Paquet and Staton. "LazyPPL: Laziness and Types in Non-Parametric Probabilistic Programs." NeurIPS 2021 Workshops: AIPLANS, 2021.

Markdown

[Paquet and Staton. "LazyPPL: Laziness and Types in Non-Parametric Probabilistic Programs." NeurIPS 2021 Workshops: AIPLANS, 2021.](https://mlanthology.org/neuripsw/2021/paquet2021neuripsw-lazyppl/)

BibTeX

@inproceedings{paquet2021neuripsw-lazyppl,
  title     = {{LazyPPL: Laziness and Types in Non-Parametric Probabilistic Programs}},
  author    = {Paquet, Hugo and Staton, Sam},
  booktitle = {NeurIPS 2021 Workshops: AIPLANS},
  year      = {2021},
  url       = {https://mlanthology.org/neuripsw/2021/paquet2021neuripsw-lazyppl/}
}