activity
20162022
most citedInferring Covariances for Probabilistic Programs

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.LO2022

A Calculus for Amortized Expected Runtimes

Kevin Batz, Benjamin Lucien Kaminski, Joost-Pieter Katoen +2

We develop a weakest-precondition-style calculus à la Dijkstra for reasoning about amortized expected runtimes of randomized algorithms with access to dynamic memory - the $\textsf…

cs.LO2022

Foundations for Entailment Checking in Quantitative Separation Logic (extended version)

Kevin Batz, Ira Fesefeldt, Marvin Jansen +4

Quantitative separation logic (QSL) is an extension of separation logic (SL) for the verification of probabilistic pointer programs. In QSL, formulae evaluate to real numbers inste…

cs.LO2020

PrIC3: Property Directed Reachability for MDPs

Kevin Batz, Sebastian Junges, Benjamin Lucien Kaminski +3

IC3 has been a leap forward in symbolic model checking. This paper proposes PrIC3 (pronounced pricy-three), a conservative extension of IC3 to symbolic model checking of MDPs. Our…

cs.LO2019

A Pre-Expectation Calculus for Probabilistic Sensitivity

Alejandro Aguirre, Gilles Barthe, Justin Hsu +3

Sensitivity properties describe how changes to the input of a program affect the output, typically by upper bounding the distance between the outputs of two runs by a monotone func…

cs.PL2018

How long, O Bayesian network, will I sample thee? A program analysis perspective on expected sampling times

Kevin Batz, Benjamin Lucien Kaminski, Joost-Pieter Katoen +1

Bayesian networks (BNs) are probabilistic graphical models for describing complex joint probability distributions. The main problem for BNs is inference: Determine the probability…

cs.LO20161 cited

Inferring Covariances for Probabilistic Programs

Benjamin Lucien Kaminski, Joost-Pieter Katoen, Christoph Matheja

We study weakest precondition reasoning about the (co)variance of outcomes and the variance of run-times of probabilistic programs with conditioning. For outcomes, we show that app…