What do posterior distributions of probabilistic programs look like? (LAFI 2023) - POPL 2023

Sun 15 - Sat 21 January 2023 Boston, Massachusetts, United States

Who

Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka, Sam Staton

Track

Time Zone

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When

Sun 15 Jan 2023 11:00 - 11:20 at Scollay - Second Session Chair(s): Steven Holtzen, Christine Tasson

Abstract

We define a natural set of base measures on $\mathbb{R}^n$, which we call s-Hausdorff, that generalize the Lebesgue measure and characterize posterior distributions of probabilistic programs – they have a density w.r.t. some s-Hausdorff measure – when the deterministic part of the language is a higher-order recursive functional language, with conditionals and partial piecewise smooth primitives.

File attachments

What do posterior distributions of probabilistic programs look like? (lafi23-final63.pdf)	282KiB

Mathieu Huot

University of Oxford

United Kingdom

Alexander K. LewAuthor

Massachusetts Institute of Technology

United States

Vikash K. Mansinghka

Massachusetts Institute of Technology

United States

Sam Staton

University of Oxford

United Kingdom

Time Zone

The program is currently displayed in (GMT-05:00) Eastern Time (US & Canada).

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The GMT offsets shown reflect the offsets at the moment of the conference.

Time Band

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Session Program

Sun 15 Jan
Displayed time zone: Eastern Time (US & Canada) change

	11:00 - 12:30	Second SessionLAFI at Scollay Chair(s): Steven Holtzen Northeastern University, Christine Tasson Sorbonne Université — LIP6

	11:00 20m Talk		What do posterior distributions of probabilistic programs look like?Boston LAFI Mathieu Huot University of Oxford, A: Alexander K. Lew Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology, Sam Staton University of Oxford File Attached
	11:20 10m Talk		Semantics of Probabilistic Program TracesBoston LAFI Alexander K. Lew Massachusetts Institute of Technology, A: Eli Sennesh Northeastern University, Jan-Willem Van De Meent University of Amsterdam, Vikash Mansinghka Massachusetts Institute of Technology File Attached
	11:30 10m Talk		A convenient category of tracing measure kernelsBoston LAFI A: Eli Sennesh Northeastern University, Jan-Willem Van De Meent University of Amsterdam File Attached
	11:45 5m Talk		Random probability distributions as natural transformationsParis LAFI A: Victor Blanchi ENS Paris, Hugo Paquet University of Oxford File Attached
	11:50 5m Talk		Static Delayed Sampling for Probabilistic Programming LanguagesParis LAFI A: Gizem Caylak KTH Royal Institute of Technology, Daniel Lundén KTH Royal Institute of Technology, Viktor Senderov Naturhistoriska riksmuseet, David Broman KTH Royal Institute of Technology
	11:55 5m Talk		Denotational semantics of languages for inference: semirings, monads, and tensorsOnline LAFI Cristina Matache University of Edinburgh, A: Sean Moss University of Oxford, Sam Staton University of Oxford, Ariadne Si Suo University of Oxford
	12:10 5m Talk		Separated and Shared Effects in Higher-Order LanguagesBoston LAFI A: Pedro Henrique Azevedo de Amorim Cornell University, Justin Hsu Cornell University
	12:15 5m Talk		On Iteration in Discrete Probabilistic ProgrammingBoston LAFI A: Mateo Torres-Ruiz , Robin Piedeleu University of Oxford, Alexandra Silva Cornell University, Fabio Zanasi University College London File Attached
	12:20 5m Talk		Bit-Blasting Probabilistic ProgramsBoston LAFI A: Poorva Garg University of California, Los Angeles, Steven Holtzen Northeastern University, Guy Van den Broeck University of California at Los Angeles, Todd Millstein University of California at Los Angeles File Attached
	12:25 5m Talk		πMPC: Automatic Security Proofs for MPC ProtocolsBoston LAFI A: Mako P. Bates University of Vermont, Joseph P. Near University of Vermont