[TYPES/announce] Workshop on probabilistic programming semantics 2017

Chung-chieh Shan ccshan at indiana.edu
Mon Oct 3 13:38:07 EDT 2016

Workshop on probabilistic programming semantics (PPS 2017)
Colocated right before POPL (Paris, France) on January 17, 2017


Call for extended abstracts

Probabilistic programming is the idea of expressing probabilistic models
and inference methods as programs, to ease use and reuse.  The recent
rise of practical implementations as well as research activity in
probabilistic programming has renewed the need for semantics to help us
share insights and innovations.

This workshop aims to bring programming-language and machine-learning
researchers together to advance the semantic foundations of probabilistic
programming.  Topics include but are not limited to:

  * the denotational semantics of probabilistic functions, open universe,
    loops, and conditioning;
  * the operational semantics of sampling, exact inference, and MCMC
  * axiomatic and equational reasoning;
  * types and polymorphism;
  * and last but not least, how semantics informs any aspect of
    probabilistic programming, be it design, theory, implementation, or

We expect this workshop to be informal, and our goal is to foster
collaboration and establish common ground.  Thus, the proceedings will not
be a formal or archival publication, and we expect to spend only a portion
of the workshop day on traditional research talks.  Nevertheless, as a
concrete basis for fruitful discussions, we call for extended abstracts
describing specific and ideally ongoing work on probabilistic programming

Extended abstracts are up to 2 pages in PDF format.  Please submit them by
October 31 using EasyChair: https://easychair.org/conferences/?conf=pps2017

Monday, October 31, 2016: Submissions due
Friday, November 18, 2016: Author notification
Friday, December 23, 2016: Final papers due
Tuesday, January 17, 2017: Workshop, colocated right before POPL

Program committee:

  * Cameron Freer, Gamalon and Borelian (chair)
  * Chung-chieh Shan, Indiana University (chair)
  * Michael Carbin, MIT
  * Johannes Hölzl, Technische Universität München
  * Avi Pfeffer, Charles River Analytics
  * Daniel Roy, University of Toronto
  * Alexandra Silva, University College London
  * Guy Steele, Oracle Labs
  * Guy Van den Broeck, UCLA

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