POPL 2018 (series) / PPS 2018 (series) / Probabilistic Programming Languages, Semantics, and Systems (PPS 2018) /
Auxiliary variables in Probabilistic Programs
We extend the first-order meta-language of Staton et al. with a new language construct, slice-let . This new construct allows a user to define a random variable x, with a potentially intractable distribution, by introducing an auxiliary random variable, u, and specifying only the conditional distributions of x given u and of u given x. In effect, the distribution of x need only be defined up to some level of approximation, determined by the value of u. We outline the denotational semantics for slice-let and give some example programs. Finally, we briefly discuss an approximate representation of the program that can be used by an inference algorithm.
Tue 9 JanDisplayed time zone: Tijuana, Baja California change
Tue 9 Jan
Displayed time zone: Tijuana, Baja California change
16:00 - 18:00 | |||
16:00 30mTalk | Auxiliary variables in Probabilistic Programs PPS | ||
16:30 30mTalk | Probabilistic Program Inference With Abstractions PPS Steven Holtzen University of California, Los Angeles, Guy Van den Broeck University of California, Los Angeles, Todd Millstein University of California, Los Angeles Pre-print | ||
17:00 30mTalk | SlicStan: Improving Probabilistic Programming using Information Flow Analysis PPS Maria I. Gorinova The University of Edinburgh, Andrew D. Gordon Microsoft Research and University of Edinburgh, Charles Sutton University of Edinburgh Pre-print | ||
17:30 30mTalk | Contextual Equivalence for a Probabilistic Language with Continuous Random Variables and Recursion PPS Mitchell Wand Northeastern University, USA, Theophilos Giannakopoulos BAE Systems, Inc., Andrew Cobb Northeastern University, Ryan Culpepper Northeastern University |