POPL 2024
Sun 14 - Sat 20 January 2024 London, United Kingdom
Sun 14 Jan 2024 14:50 - 15:00 at Kelvin Lecture - Third Session Chair(s): Steven Holtzen, Matthijs Vákár

Lilac is a probabilistic separation logic whose separating conjunction denotes probabilistic independence. In contrast to ordinary separation logic, where propositions denote properties of heaps and separating conjunction splits heaps into disjoint subheaps, Lilac propositions denote properties of probability spaces and separating conjunction splits probability spaces into independent subspaces. Naively, one would expect this splitting of probability spaces to be defined in terms of product spaces, but this is not so. Instead, Lilac’s separating conjunction is defined in terms of independent combination, a partial binary operation on probability spaces that plays the role disjoint union does for heaps in ordinary separation logic. The definition of independent combination does not mention product spaces at all; rather, independent combination is constructed out of low-level measure-theoretic objects. This disconnect between independent combination and the familiar product space construction is puzzling to those well-versed in probability theory: how do we know that independent combination provides the right notion of separation for probabilistic separation logic?

To answer this question, we first construct two categories: one category equipped with a model of core Lilac where separation is defined via independent combination, and one category equipped with a model of core Lilac where separation is defined via product. Our answer then comes in the form of a theorem: these two categories are equivalent, and the notion of separation in one category corresponds to the notion of separation in the other across this equivalence, showing that independent combination and product are two equivalent points of view on the same underlying probability-theoretic concept. In addition to justifying the use of independent combination in Lilac’s semantic model, our equivalence theorem creates connections between probability theory and nominal sets: it is a probabilistic analogue of a classic theorem of topos theory, showing that the category of nominal sets is equivalent to a suitable category of sheaves.

Towards a Categorical Model of the Lilac Separation Logic (categorical-lilac.pdf)446KiB

Sun 14 Jan

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14:00 - 15:30
Third SessionLAFI at Kelvin Lecture
Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University
14:00
10m
Talk
Effect Handlers for Choice-Based Learning
LAFI
Gordon Plotkin Google, Ningning Xie University of Toronto
File Attached
14:10
10m
Talk
Guaranteed Bounds for Discrete Probabilistic Programs with Loops via Generating Functions
LAFI
Fabian Zaiser University of Oxford, Andrzej Murawski University of Oxford, C.-H. Luke Ong NTU
File Attached
14:20
10m
Talk
JuliaBUGS: A Graph-Based Probabilistic Programming Language using BUGS syntax
LAFI
Xianda Sun University of Cambridge, Philipp Gabler Independent researcher, Andrew Thomas University of Cambridge, Hong Ge University of Cambridge
14:30
10m
Talk
Mixture Languages
LAFI
Oliver Richardson Cornell University, Jialu Bao Cornell University
File Attached
14:40
10m
Talk
Structured Tensor Algebra for Efficient Discrete Probabilistic Inference
LAFI
Amir Shaikhha University of Edinburgh
14:50
10m
Talk
Towards a Categorical Model of the Lilac Separation Logic
LAFI
John Li Northeastern University, Jon Aytac Sandia National Laboratories, Philip Johnson-Freyd Sandia National Laboratories, Amal Ahmed Northeastern University, USA, Steven Holtzen Northeastern University
File Attached
15:00
10m
Talk
Toward Probabilistic Coarse-to-Fine Program Synthesis
LAFI
Maddy Bowers Massachusetts Institute of Technology, Alexander K. Lew Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology, Joshua B. Tenenbaum Massachusetts Institute of Technology, Armando Solar-Lezama Massachusetts Institute of Technology
15:10
10m
Talk
Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial SolvingOnline
LAFI
Peixin Wang University of Oxford, Hongfei Fu Shanghai Jiao Tong University, Tengshun Yang SKLCS, Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Guanyan Li University of Oxford, C.-H. Luke Ong NTU
15:20
10m
Talk
Abstract Interpretation for Automatic DifferentiationOnline
LAFI
Jacob Laurel University of Illinois at Urbana-Champaign, Siyuan Brant Qian University of Illinois at Urbana-Champaign; Zhejiang University, Gagandeep Singh University of Illinois at Urbana-Champaign; VMware Research, Sasa Misailovic University of Illinois at Urbana-Champaign