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Jon Aytac

dblp:228/9398 · also Jon M. Aytac · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-9734-5747ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Logic in computer science · 75% Automated reasoning and model checking · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Logic in computer science
categorical semantics
0.812024
A Nominal Approach to Probabilistic Separation Logic · LICS 2024
Logic in computer science
nominal sets
0.812024
A Nominal Approach to Probabilistic Separation Logic · LICS 2024
Automated reasoning and model checking
program verification
0.812024
A Nominal Approach to Probabilistic Separation Logic · LICS 2024
Logic in computer science › program logic
separation logic
0.812024
A Nominal Approach to Probabilistic Separation Logic · LICS 2024

Methods — techniques the papers use, named apart from their topics

schanuel topos · 0.8measure theory · 0.8category theory · 0.8
YearPublicationVenuePosition
2024 A Nominal Approach to Probabilistic Separation Logic
abstract
Currently, there is a gap between the tools used by probability theorists and those used in formal reasoning about probabilistic programs. On the one hand, a probability theorist decomposes probabilistic state along the simple and natural product of probability spaces. On the other hand, recently developed probabilistic separation logics decompose state via relatively unfamiliar measure-theoretic constructions for computing unions of sigma-algebras and probability measures. We bridge the gap between these two perspectives by showing that these two methods of decomposition are equivalent up to a suitable equivalence of categories. Our main result is a probabilistic analog of the classic equivalence between the category of nominal sets and the Schanuel topos. Through this equivalence, we validate design decisions in prior work on probabilistic separation logic and create new connections to nominal-setlike models of probability.
John M. Li, Jon Aytac, Philip Johnson-Freyd, Amal Ahmed 0001, Steven Holtzen
LICS2