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PLDI 2020
Mon 15 - Fri 19 June 2020

We present $\lambda$PSI, the first probabilistic programming language and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuous and mixed random variables. $\lambda$PSI's solver is based on symbolic reasoning and computes the exact distribution represented by a program.

We show that $\lambda$PSI is practically effective—it automatically computes exact distributions for a number of interesting applications, from rational agents to information theory, many of which could so far only be handled approximately.

Fri 19 Jun

Displayed time zone: Pacific Time (US & Canada) change

05:00 - 06:00
Probabilistic ProgrammingPLDI Research Papers at PLDI Research Papers live stream
Chair(s): Sasa Misailovic University of Illinois at Urbana-Champaign

YouTube lightning session video

Proving Almost-Sure Termination by Omega-Regular Decomposition
PLDI Research Papers
Jianhui Chen Tsinghua University, China, Fei He Tsinghua University, China
λPSI: Exact Inference for Higher-Order Probabilistic Programs
PLDI Research Papers
Timon Gehr ETH Zurich, Switzerland, Samuel Steffen ETH Zurich, Switzerland, Martin Vechev ETH Zurich, Switzerland
Reactive Probabilistic Programming
PLDI Research Papers
Guillaume Baudart IBM Research, Louis Mandel IBM Research, Eric Atkinson Massachusetts Institute of Technology, USA, Benjamin Sherman Massachusetts Institute of Technology, USA, Marc Pouzet École normale supérieure, Michael Carbin Massachusetts Institute of Technology, USA
DOI Pre-print Media Attached