We define a notion of stable and measurable map between cones endowed with
measurability tests and show that it forms a cpo-enriched cartesian closed category. This …

This paper presents a new language for network programming based on a probabilistic
semantics. We extend the NetKATlanguage with new primitives for expressing probabilistic …

Wir studieren die quantitative Analyse probabilistischer Programme. Dabei untersuchen wir
vornehmlich zwei Aspekte: Die Analysetechniken selbst, sowie die komplexitäts-bzw …

Combining probabilistic choice and non-determinism is a long standing problem in
denotational semantics. From a category theory perspective, the problem stems from the …

Programs increasingly rely on randomization in applications such as cryptography and
machine learning. Analyzing randomized programs has been a fruitful research direction …

We present Polaris, a concurrent separation logic with support for probabilistic reasoning. As
part of our logic, we extend the idea of coupling, which underlies recent work on probabilistic …

We consider mixed powerdomains combining ordinary nondeterminism and probabilistic
nondeterminism. We characterise them as free algebras for suitable (in) equation-al …

ProbNetKAT is a probabilistic extension of NetKAT with a denotational semantics based on
Markov kernels. The language is expressive enough to generate continuous distributions …

Automatically establishing that a probabilistic program satisfies some property ϕ is a
challenging problem. While a sampling-based approach—which involves running the …

Probabilistic programming provides a convenient lingua franca for writing succinct and
rigorous descriptions of probabilistic models and inference tasks. Several probabilistic …