Comparing the speed of probabilistic processes ( PPS 2018 - Probabilistic Programming Languages, Semantics, and Systems (PPS 2018))

Who

Mathias Ruggaard Pedersen, Nathanaël Fijalkow, Giorgio Bacci, Kim Larsen, Radu Mardare

Track

PPS 2018

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When

Tue 9 Jan 2018 10:08 - 10:10 at Bradbury - POSTER SESSION (14 posters - not talks)

Abstract

blah blah blah

Mathias Ruggaard Pedersen

Aalborg University

Nathanaël Fijalkow

Alan Turing Institute

Giorgio Bacci

Aalborg University

Kim Larsen

Aalborg University

Denmark

Radu Mardare

Aalborg University

Denmark

Time Zone

The program is currently displayed in (GMT-08:00) Tijuana, Baja California.

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Session Program

Tue 9 Jan
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10:00 - 10:30	POSTER SESSION (14 posters - not talks) PPS at Bradbury

10:00 2m Talk		Probabilistic Programming for Robotics PPS Nils Napp SUNY at Buffalo, Marco Gaboardi University at Buffalo, SUNY
10:02 2m Talk		Game Semantics for Probabilistic Programs PPS C.-H. Luke Ong University of Oxford, Matthijs Vákár University of Oxford
10:04 2m Talk		Interactive Writing and Debugging of Bayesian Probabilistic Programs PPS Javier Burroni , Arjun Guha University of Massachusetts, Amherst, David Jensen University of Massachusetts Amherst Pre-print
10:06 2m Talk		Deep Amortized Inference for Probabilistic Programs using Adversarial Compilation PPS Mahdi Azarafrooz Cylance
10:08 2m Talk		Comparing the speed of probabilistic processes PPS Mathias Ruggaard Pedersen Aalborg University, Nathanaël Fijalkow Alan Turing Institute, Giorgio Bacci Aalborg University, Kim Larsen Aalborg University, Radu Mardare Aalborg University
10:10 2m Talk		Using Reinforcement Learning for Probabilistic Program Inference PPS Avi Pfeffer Charles River Analytics
10:12 2m Talk		TensorFlow Distributions PPS Joshua V. Dillon Google, Ian Langmore Google, Eugene Brevdo Google, Matt Hoffman Google, Dave Moore Google, Brian Patton Google, Rif A. Saurous Google, Dustin Tran , Srinivas Vasudevan Google Link to publication Pre-print
10:15 2m Talk		Constructive probabilistic semantics with non-spatial locales PPS Benjamin Sherman Massachusetts Institute of Technology, USA, Jared Tramontano Massachusetts Institute of Technology, Michael Carbin MIT Pre-print
10:17 2m Talk		Using probabilistic programs as proposals PPS Marco Cusumano-Towner MIT-CSAIL, Vikash Mansinghka Massachusetts Institute of Technology
10:19 2m Talk		Probabilistic Program Equivalence for NetKAT PPS Steffen Smolka Cornell University, David Kahn Cornell University, Praveen Kumar Cornell University, Nate Foster Cornell University, Dexter Kozen , Alexandra Silva University College London Link to publication File Attached
10:21 2m Talk		Reasoning about Divergences via Span-liftings PPS Tetsuya Sato University at Buffalo, SUNY, USA
10:23 2m Talk		Probabilistic Models for Assured Position, Navigation and Timing PPS Andres Molina-Markham The MITRE Corporation
10:25 2m Talk		The Support Method of Computing Expectations PPS Avi Pfeffer Charles River Analytics
10:27 2m Talk		Combining static and dynamic optimizations using closed-form solutions PPS Daniel Lundén KTH Royal Institute of Technology, David Broman KTH Royal Institute of Technology, Lawrence M. Murray Uppsala University