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Sat 23 Jan 2016 17:00 - 17:20 at Room St Petersburg II - Session 5 Chair(s): Chung-chieh Shan

Our attempt to give semantics to a core, functional probabilistic programming language uses computable distributions. The semantics uses largely standard techniques from denotational semantics. One nice property of computable distributions is that they are completely characterized by a sampling algorithm. Hence, it is possible to faithfully implement (in a Turing-complete language) a semantics based on computable distributions as a sampling library. We are interested in the pros and cons of using computable distributions as opposed to measure theory in giving semantics to probabilistic programming languages.

Sat 23 Jan

Displayed time zone: Guadalajara, Mexico City, Monterrey change

16:30 - 18:00
Session 5PPS at Room St Petersburg II
Chair(s): Chung-chieh Shan Indiana University
16:30
20m
Talk
eXchangeable Random Primitives
PPS
Nathanael L. Ackerman Harvard University, Cameron Freer Gamalon, Daniel Roy University 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 Huang Harvard University, Greg Morrisett Cornell University
Pre-print
17:20
10m
Meeting
Discussion 9
PPS

17:30
20m
Talk
On The Semantic Intricacies of Conditioning
PPS
Friedrich Gretz RWTH Aachen University, Nils Jansen RWTH Aachen University, Benjamin Lucien Kaminski RWTH Aachen University, Joost-Pieter Katoen RWTH Aachen University, Federico Olmedo RWTH Aachen University
Pre-print
17:50
10m
Meeting
Discussion 10
PPS