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Workshop on probabilistic programming semantics

Probabilistic programming is the idea of expressing probabilistic models and inference methods as programs and transformations, 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 transitions;
  • 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 applications.

Discussion guidelines for speakers and other participants

This workshop aims to bring programming-language and machine-learning researchers together. The accepted presentations are gathered at http://pps2016.soic.indiana.edu/. The blog format there invites everyone to ask questions and leave comments before and after the in-person workshop. Or read the abstracts and bring your questions!

To foster collaboration and establish common ground, the posters, the discussion period after each talk, and the breaks are crucial. If you are giving a talk, please abide by the time limit of 20 minutes, and consider encouraging clarification questions during your talk. Each discussion period is 10 minutes—longer than usual, because interaction is key. Please ask questions.

Because probabilistic programming is a research area that bridges multiple communities with different vocabularies, it is especially useful for everyone to ask questions like “What do you mean by X?” and “How is X useful to you?”, where X is a term that occurs in a presentation. Of course, it is also useful for presenters to explain terms proactively.

If you are in the workshop room during a talk, please give the speaker your full attention. Otherwise, please enjoy the posters and snacks in the hallway. We accepted 10 submissions as posters and 10 as talks, not on the basis of reviewer scores but based on which medium we thought would be most effective in conveying the material. So, some highly ranked submissions that are more technical in nature are accepted as posters.

Accepted extended abstracts

Title
A Denotational Semantics of a Probabilistic Stream-Processing Language
PPS
Pre-print
A Lambda-Calculus Foundation for Universal Probabilistic Programming
PPS
Pre-print
All You Need is the Monad... What Monad Was That Again?
PPS
Pre-print
An Application of Computable Distributions to the Semantics of Probabilistic Programs
PPS
Pre-print
An Interface for Black Box Learning in Probabilistic Programs
PPS
Pre-print
Coalgebraic Trace Semantics for Probabilistic Processes: Preliminary Proposal
PPS
Pre-print
Finite-depth Higher-order Abstract Syntax Trees for Reasoning about Probabilistic Programs
PPS
Pre-print
Fixed Points for Markov Decision Processes
PPS
Pre-print
Insomnia: Types and Modules for Probabilistic Programming
PPS
Pre-print
Making our Own Luck: A Language for Random Generators
PPS
Pre-print
Models for Probabilistic Programs with an Adversary
PPS
Pre-print
Observation Propagation for Importance Sampling with Likelihood Weighting
PPS
Pre-print
On The Semantic Intricacies of Conditioning
PPS
Pre-print
Parameterized Probability Monad
PPS
Pre-print
Problems of the Lightweight Implementation of Probabilistic Programming
PPS
Pre-print
Reasoning about Probability and Nondeterminism
PPS
Pre-print
Reproducing Kernel Hilbert Space Semantics for Probabilistic Programs
PPS
Pre-print
Semantics of Higher-order Probabilistic Programs
PPS
Pre-print
The Semantics of Figaro, an Embedded Probabilistic Programming Language
PPS
Pre-print
eXchangeable Random Primitives
PPS
Pre-print

Call for extended abstracts

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 semantics.

Extended abstracts are up to 2 pages in PDF format. Please submit them by October 16 using EasyChair: https://easychair.org/conferences/?conf=pps2016

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Sat 23 Jan
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09:00 - 10:00
Session 1PPS at Room St Petersburg II
Chair(s): Cameron FreerGamalon
09:00
20m
Talk
All You Need is the Monad... What Monad Was That Again?
PPS
Pre-print
09:20
10m
Meeting
Discussion 1
PPS
09:30
20m
Talk
An Interface for Black Box Learning in Probabilistic Programs
PPS
Jan-Willem van de MeentUniversity of Oxford, Brooks PaigeUniversity of Oxford, David TolpinUniversity of Oxford, Frank WoodUniversity of Oxford
Pre-print
09:50
10m
Meeting
Discussion 2
PPS
10:30 - 12:15
Session 2PPS at Room St Petersburg II
Chair(s): Chad ScherrerGalois, Inc.
10:30
20m
Talk
Models for Probabilistic Programs with an Adversary
PPS
Robert RandUniversity of Pennsylvania, Steve ZdancewicUniversity of Pennsylvania
Pre-print
10:50
10m
Meeting
DIscussion 3
PPS
11:00
20m
Talk
The Semantics of Figaro, an Embedded Probabilistic Programming Language
PPS
Avi PfefferCharles River Analytics, Brian RuttenbergCharles River Analytics
Pre-print
11:20
10m
Meeting
Discussion 4
PPS
11:30
45m
Meeting
Implementor Panel: What can semantics do for probabilistic programming and what can probabilistic programming do for semantics?
PPS
Angelika KimmigKU Leuven, Oleg Kiselyov, Jan-Willem van de MeentUniversity of Oxford, Avi PfefferCharles River Analytics, M: Frank WoodUniversity of Oxford
14:00 - 15:30
Session 3PPS at Room St Petersburg II
Chair(s): Mitchell WandNortheastern University
14:00
20m
Talk
A Lambda-Calculus Foundation for Universal Probabilistic Programming
PPS
Johannes BorgströmUppsala University, Ugo Dal LagoUniversity of Bologna, Andrew D. GordonMicrosoft Research and University of Edinburgh, Marcin SzymczakUniversity of Edinburgh
Pre-print
14:20
10m
Meeting
Discussion 5
PPS
14:30
20m
Talk
Making our Own Luck: A Language for Random Generators
PPS
Leonidas LampropoulosUniversity of Pennsylvania, Benjamin C. PierceUniversity of Pennsylvania, Cătălin HriţcuINRIA Paris, John HughesChalmers University of Technology, Zoe ParaskevopoulouPrinceton University, Li-yao XiaENS Paris
Pre-print
14:50
10m
Meeting
Discussion 6
PPS
15:00
20m
Talk
Semantics of Higher-order Probabilistic Programs
PPS
Sam StatonUniversity of Oxford, Hongseok YangUniversity of Oxford, UK, Chris HeunenUniversity of Edinburgh, Ohad KammarUniversity of Cambridge, Frank WoodUniversity of Oxford
Pre-print
15:20
10m
Meeting
Discussion 7
PPS
15:30 - 16:30
Poster SessionPPS at Room St Petersburg II
15:30
60m
Meeting
Insomnia: Types and Modules for Probabilistic Programming
PPS
Aleksey KligerXamarin, Inc., Sean StromstenBAE Systems, Inc.
Pre-print
15:30
60m
Meeting
Finite-depth Higher-order Abstract Syntax Trees for Reasoning about Probabilistic Programs
PPS
Theophilos GiannakopoulosBAE Systems, Inc., Mitchell WandNortheastern University, Andrew CobbNortheastern University
Pre-print
15:30
60m
Meeting
Coalgebraic Trace Semantics for Probabilistic Processes: Preliminary Proposal
PPS
Larry MossIndiana University, Chung-chieh ShanIndiana University, Alexandra SilvaRadboud University Nijmegen
Pre-print
15:30
60m
Meeting
Reasoning about Probability and Nondeterminism
PPS
Faris Abou-SalehUniversity of Oxford, Kwok-Ho CheungUniversity of Oxford, Jeremy GibbonsUniversity of Oxford, UK
Pre-print
15:30
60m
Meeting
Fixed Points for Markov Decision Processes
PPS
Johannes HölzlTechnische Universität München
Pre-print
15:30
60m
Meeting
A Denotational Semantics of a Probabilistic Stream-Processing Language
PPS
Yohei MiyamotoGraduate School of Informatics, Kyoto University, Kohei Suenaga, Koji NakazawaGraduate School of Information Science, Nagoya University
Pre-print
15:30
60m
Meeting
Observation Propagation for Importance Sampling with Likelihood Weighting
PPS
Ryan CulpepperNortheastern University
Pre-print
15:30
60m
Meeting
Problems of the Lightweight Implementation of Probabilistic Programming
PPS
Pre-print
15:30
60m
Meeting
Parameterized Probability Monad
PPS
Adam ŚcibiorUniversity of Cambridge, Andrew D. GordonMicrosoft Research and University of Edinburgh
Pre-print
15:30
60m
Meeting
Reproducing Kernel Hilbert Space Semantics for Probabilistic Programs
PPS
Adam ŚcibiorUniversity of Cambridge, Bernhard SchölkopfMPI Tuebingen
Pre-print
16:30 - 18:00
Session 5PPS at Room St Petersburg II
Chair(s): Chung-chieh ShanIndiana University
16:30
20m
Talk
eXchangeable Random Primitives
PPS
Nathanael L. AckermanHarvard University, Cameron FreerGamalon, Daniel RoyUniversity of Toronto
Pre-print
16:50
10m
Meeting
Discussion 8
PPS
17:00
20m
Talk
An Application of Computable Distributions to the Semantics of Probabilistic Programs
PPS
Daniel HuangHarvard University, Greg MorrisettCornell University
Pre-print
17:20
10m
Meeting
Discussion 9
PPS
17:30
20m
Talk
On The Semantic Intricacies of Conditioning
PPS
Friedrich GretzRWTH Aachen University, Nils JansenRWTH Aachen University, Benjamin Lucien KaminskiRWTH Aachen University, Joost-Pieter KatoenRWTH Aachen University, Federico OlmedoRWTH Aachen University
Pre-print
17:50
10m
Meeting
Discussion 10
PPS