activity
20132020
most citedMeasure Transformer Semantics for Bayesian Machine Learning

31 citations · 45 across the 7 of their papers we have counts for

collaborators

7 papers

cs.PL2020★ 7 cited

Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages

Daniel Lundén, Johannes Borgström, David Broman

Probabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic progra…

cs.LO2019★ 4 cited

Modal Logics for Nominal Transition Systems

Joachim Parrow, Johannes Borgström, Lars-Henrik Eriksson +2

We define a general notion of transition system where states and action labels can be from arbitrary nominal sets, actions may bind names, and state predicates from an arbitrary lo…

cs.PL2017★ 3 cited

Deriving Probability Density Functions from Probabilistic Functional Programs

Sooraj Bhat, Johannes Borgström, Andrew D. Gordon +1

The probability density function of a probability distribution is a fundamental concept in probability theory and a key ingredient in various widely used machine learning methods.…

cs.PL2015

A Lambda-Calculus Foundation for Universal Probabilistic Programming

Johannes Borgström, Ugo Dal Lago, Andrew D. Gordon +1

We develop the operational semantics of an untyped probabilistic lambda-calculus with continuous distributions, as a foundation for universal probabilistic programming languages su…

cs.LO2014

Proceedings Combined 21st International Workshop on Expressiveness in Concurrency and 11th Workshop on Structural Operational Semantics

Johannes Borgström, Silvia Crafa

This volume contains the proceedings of the Combined 21st International Workshop on Expressiveness in Concurrency and the 11th Workshop on Structural Operational Semantics (EXPRESS…

cs.LO2013★ 31 cited

Measure Transformer Semantics for Bayesian Machine Learning

Johannes Borgström, Andrew D Gordon, Michael Greenberg +2

The Bayesian approach to machine learning amounts to computing posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a p…

cs.PL2013

Proceedings Combined 20th International Workshop on Expressiveness in Concurrency and 10th Workshop on Structural Operational Semantics

Johannes Borgström, Bas Luttik

This volume contains the proceedings of the Combined 20th International Workshop on Expressiveness in Concurrency and the 10th Workshop on Structural Operational Semantics (EXPRESS…