Stochastic memoization is a higher-order construct of probabilistic
prog...
We introduce a new setting, the category of ωPAP spaces, for reasoning
d...
We show that streams and lazy data structures are a natural idiom for
pr...
Optimizing the expected values of probabilistic processes is a central
p...
De Finetti theorems tell us that if we expect the likelihood of outcomes...
We study concrete sheaf models for a call-by-value higher-order language...
We consider a bag (multiset) monad on the category of standard Borel spa...
We present a fully abstract model of a call-by-value language with
highe...
We define a probabilistic programming language for Gaussian random varia...
A point process on a space is a random bag of elements of that space. In...
We present semantic correctness proofs of automatic differentiation (AD)...
We make a formal analogy between random sampling and fresh name generati...
We present semantic correctness proofs of Automatic Differentiation (AD)...
We propose a categorical foundation for the connection between pure and ...
We argue that notions in quantum theory should have universal properties...
Motivated by problems in Bayesian nonparametrics and probabilistic
progr...
We give an adequate denotational semantics for languages with recursive
...
In this paper we analyze the Beta-Bernoulli process from Bayesian
nonpar...
We describe categorical models of a circuit-based (quantum) functional p...
We present a modular semantic account of Bayesian inference algorithms f...
Higher-order probabilistic programming languages allow programmers to wr...
We study the semantic foundation of expressive probabilistic programming...