no code implementations • EMNLP (NLP+CSS) 2020 • Bertie Vidgen, Scott Hale, Sam Staton, Tom Melham, Helen Margetts, Ohad Kammar, Marcin Szymczak
We investigate the use of machine learning classifiers for detecting online abuse in empirical research.
no code implementations • 21 Feb 2023 • Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka, Sam Staton
We introduce a new setting, the category of $\omega$PAP spaces, for reasoning denotationally about expressive differentiable and probabilistic programming languages.
no code implementations • NeurIPS Workshop AIPLANS 2021 • Hugo Paquet, Sam Staton
We introduce LazyPPL, a prototype probabilistic programming library for Haskell.
1 code implementation • 27 Jan 2021 • Dario Stein, Sam Staton
We define a probabilistic programming language for Gaussian random variables with a first-class exact conditioning construct.
no code implementations • 10 Jan 2017 • Chris Heunen, Ohad Kammar, Sam Staton, Hongseok Yang
Higher-order probabilistic programming languages allow programmers to write sophisticated models in machine learning and statistics in a succinct and structured way, but step outside the standard measure-theoretic formalization of probability theory.
no code implementations • 19 Jan 2016 • Sam Staton, Hongseok Yang, Chris Heunen, Ohad Kammar, Frank Wood
We study the semantic foundation of expressive probabilistic programming languages, that support higher-order functions, continuous distributions, and soft constraints (such as Anglican, Church, and Venture).
no code implementations • 21 Jan 2011 • Sam Staton
The theory of coalgebras, for an endofunctor on a category, has been proposed as a general theory of transition systems.
Logic in Computer Science F.3.2, G.2.m