Blogs (1) >>
POPL 2019
Sun 13 - Sat 19 January 2019 Cascais, Portugal
Wed 16 Jan 2019 13:45 - 14:07 at Sala I - Probabilistic Programming and Semantics Chair(s): Justin Hsu

Stan is a probabilistic programming language that has been increasingly used for real-world scalable projects. However, to make practical inference possible, the language sacrifices some of its usability by adopting a block syntax, which lacks compositionality and flexible user-defined functions. Moreover, the semantics of the language has been mainly given in terms of intuition about implementation, and has not been formalised.

This paper provides a formal treatment of the Stan language, and introduces the probabilistic programming language SlicStan — a compositional, self-optimising version of Stan. Our main contributions are: (1) the formalisation of a core subset of Stan through an operational density-based semantics; (2) the design and semantics of the Stan-like language SlicStan, which facilities better code reuse and abstraction through its compositional syntax, more flexible functions, and information-flow type system; and (3) a formal, semantic-preserving procedure for translating SlicStan to Stan.

Wed 16 Jan

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13:45 - 14:51
Probabilistic Programming and SemanticsResearch Papers at Sala I
Chair(s): Justin Hsu University of Wisconsin-Madison, USA
13:45
22m
Talk
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic
Research Papers
Maria I. Gorinova The University of Edinburgh, Andrew D. Gordon Microsoft Research and University of Edinburgh, Charles Sutton University of Edinburgh
Link to publication DOI Pre-print Media Attached File Attached
14:07
22m
Talk
A Domain Theory for Statistical Probabilistic ProgrammingDistinguished Paper
Research Papers
Matthijs Vákár University of Oxford, Ohad Kammar University of Edinburgh, Sam Staton University of Oxford
Link to publication DOI Pre-print Media Attached File Attached
14:29
22m
Talk
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling
Research Papers
Feras Saad Massachusetts Institute of Technology, Marco Cusumano-Towner MIT-CSAIL, Ulrich Schaechtle Massachusetts Institute of Technology, USA, Martin C. Rinard Massachusetts Institute of Technology, Vikash K. Mansinghka MIT
Link to publication DOI Media Attached File Attached