Mon 24 Jun 2019 14:40 - 15:00 at 224AB - Probabilistic Programming Chair(s): Martin Hirzel

Although probabilistic programming is widely used for some restricted classes of statistical models, existing systems lack the flexibility and efficiency needed for practical use with more challenging models arising in fields like computer vision and robotics. This paper introduces Gen, a general-purpose probabilistic programming system that achieves modeling flexibility and inference efficiency via several novel language constructs: (i) the generative function interface for encapsulating probabilistic models; (ii) interoperable modeling languages that strike different flexibility/efficiency trade-offs; (iii) combinators that exploit common patterns of conditional independence; and (iv) an inference library that empowers users to implement efficient inference algorithms at a high level of abstraction. We show that Gen outperforms state-of-the-art probabilistic programming systems, sometimes by multiple orders of magnitude, on diverse problems including object tracking, estimating 3D body pose from a depth image, and inferring the structure of a time series.

Mon 24 Jun

pldi-2019-papers
14:00 - 15:30: PLDI Research Papers - Probabilistic Programming at 224AB
Chair(s): Martin HirzelIBM Research
pldi-2019-papers14:00 - 14:20
Talk
Steffen SmolkaCornell University, Praveen KumarCornell University, David M. KahnCarnegie Mellon University, USA, Nate FosterCornell University, Justin HsuUniversity of Wisconsin-Madison, USA, Dexter KozenCornell University, Alexandra SilvaUniversity College London
DOI Pre-print Media Attached
pldi-2019-papers14:20 - 14:40
Talk
Peixin WangShanghai Jiao Tong University, Hongfei FuIST Austria, Amir Kafshdar GoharshadyIST Austria, Krishnendu ChatterjeeIST Austria, Xudong QinEast China Normal University, China, Wenjun ShiEast China Normal University, China
Media Attached
pldi-2019-papers14:40 - 15:00
Talk
Marco Cusumano-TownerMIT-CSAIL, Feras SaadMassachusetts Institute of Technology, Alexander K. LewMassachusetts Institute of Technology, USA, Vikash MansinghkaMIT
Media Attached
pldi-2019-papers15:00 - 15:20
Talk
Jieyuan ZhangUNSW, Australia, Jingling XueUNSW Sydney
Media Attached