2 citations · 3 across the 13 of their papers we have counts for
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Cambria: Resource Abstraction for Parametrized Algebraic Effects and Handlers
Jack Liell-Cock, Sam Staton
The algebraic effects and handlers paradigm separates the concerns of the interface and implementation of computational effects in programming languages. We present Cambria, a lang…
Hippogriff: a semantic approach to uniting core and modules
Owen Lynch, Sam Staton
In this paper we introduce Hippogriff, a language with a module system that unifies syntax between the core level and the module level. Hippogriff's type theory is dependent, with…
Imprecise Probabilistic Programming, Precisely: Credal Sets via Graded Monads, BDDs, and Semiring-Parametric Inference (Functional Pearl)
Jack Liell-Cock, Sam Staton
Imprecise probability generalizes standard probability theory by replacing a single distribution with a convex set of possible distributions. We show that this generalization requi…
An Equational Axiomatization of Dynamic Threads via Algebraic Effects: Presheaves on Finite Relations, Labelled Posets, and Parameterized Algebraic Theories
Ohad Kammar, Jack Liell-Cock, Sam Lindley +2
We use the theory of algebraic effects to give a complete equational axiomatization for dynamic threads. Our method is based on parameterized algebraic theories, which give a concr…
The Relative Monadic Metalanguage
Jack Liell-Cock, Zev Shirazi, Sam Staton
Relative monads provide a controlled view of computation. We generalise the monadic metalanguage to a relative setting and give a complete semantics with strong relative monads. Ad…
Scoped Effects as Parameterized Algebraic Theories
Cristina Matache, Sam Lindley, Sean Moss +3
Notions of computation can be modelled by monads. Algebraic effects offer a characterization of monads in terms of algebraic operations and equational axioms, where operations are…
Probabilistic Programming with Exact Conditions
Dario Stein, Sam Staton
We spell out the paradigm of exact conditioning as an intuitive and powerful way of conditioning on observations in probabilistic programs. This is contrasted with likelihood-based…