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The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in the quantized, discrete parameter space created by these…

Machine Learning · Computer Science 2025-08-20 Aleksanteri Sladek , Martin Trapp , Arno Solin

We consider deep multivariate models for heterogeneous collections of random variables. In the context of computer vision, such collections may e.g. consist of images, segmentations, image attributes, and latent variables. When developing…

Machine Learning · Computer Science 2026-02-03 Dmitrij Schlesinger , Boris Flach , Alexander Shekhovtsov

We study the nature of applicative bisimilarity in $\lambda$-calculi endowed with operators for sampling from continuous distributions. On the one hand, we show that bisimilarity, logical equivalence, and testing equivalence all coincide…

Logic in Computer Science · Computer Science 2022-07-22 Gilles Barthe , Raphaëlle Crubillé , Ugo Dal Lago , Francesco Gavazzo

Recursive calls over recursive data are useful for generating probability distributions, and probabilistic programming allows computations over these distributions to be expressed in a modular and intuitive way. Exact inference is also…

Programming Languages · Computer Science 2023-03-28 David Chiang , Colin McDonald , Chung-chieh Shan

We initiate the study of parallel quantum programming by defining the operational and denotational semantics of parallel quantum programs. The technical contributions of this paper include: (1) find a series of useful proof rules for…

Logic in Computer Science · Computer Science 2019-10-02 Mingsheng Ying , Li Zhou , Yangjia Li

We discuss the relationship between discrete-time processes (chains) and one-dimensional Gibbs measures. We consider finite-alphabet (finite-spin) systems, possibly with a grammar (exclusion rule). We establish conditions for a stochastic…

Probability · Mathematics 2007-05-23 Roberto Fernandez , Gregory Maillard

The ALEA Coq library formalizes measure theory based on a variant of the Giry monad on the category of sets. This enables the interpretation of a probabilistic programming language with primitives for sampling from discrete distributions.…

Logic in Computer Science · Computer Science 2022-05-17 Martin E. Bidlingmaier , Florian Faissole , Bas Spitters

The probabilistic (or quantitative) modal mu-calculus is a fixed-point logic de- signed for expressing properties of probabilistic labeled transition systems (PLTS). Two semantics have been studied for this logic, both assigning to every…

Logic in Computer Science · Computer Science 2015-07-01 Matteo Mio

In this paper we prove that all the existing conditional event algebras embed into a three-valued extension of temporal logic of discrete past time, which the authors of this paper have proposed in anothe paper as a general model of…

Artificial Intelligence · Computer Science 2007-05-23 Jerzy Tyszkiewicz , Achim Hoffmann , Arthur Ramer

We present new techniques for automatically constructing probabilistic programs for data analysis, interpretation, and prediction. These techniques work with probabilistic domain-specific data modeling languages that capture key properties…

Programming Languages · Computer Science 2019-07-16 Feras A. Saad , Marco F. Cusumano-Towner , Ulrich Schaechtle , Martin C. Rinard , Vikash K. Mansinghka

There are several ways to define program equivalence for functional programs with algebraic effects. We consider two complementing ways to specify behavioural equivalence. One way is to specify a set of axiomatic equations, and allow proof…

Logic in Computer Science · Computer Science 2020-05-04 Niels Voorneveld

A predictive distribution over a sequence of $N+1$ events is said to be "frequency mimicking" whenever the probability for the final event conditioned on the outcome of the first $N$ events equals the relative frequency of successes among…

Methodology · Statistics 2019-09-06 Frank Lad , Giuseppe Sanfilippo

Computing the posterior distribution of a probabilistic program is a hard task for which no one-fit-for-all solution exists. We propose Gaussian Semantics, which approximates the exact probabilistic semantics of a bounded program by means…

Programming Languages · Computer Science 2023-11-15 Francesca Randone , Luca Bortolussi , Emilio Incerto , Mirco Tribastone

We consider the problem of refuting equivalence of probabilistic programs, i.e., the problem of proving that two probabilistic programs induce different output distributions. We study this problem in the context of programs with…

Programming Languages · Computer Science 2025-01-14 Krishnendu Chatterjee , Ehsan Kafshdar Goharshady , Petr Novotný , Đorđe Žikelić

The paper is a sketch of systematic presentation of distributional limit theorems and their refinements for compound sums. When analyzing, e.g., ergodic semi-Markov systems with discrete or continuous time, this allows us to separate those…

Probability · Mathematics 2024-04-29 Vsevolod K. Malinovskii

This paper introduces and studies the sequential composition and decomposition of propositional logic programs. We show that acyclic programs can be decomposed into single-rule programs and provide a general decomposition result for…

Logic in Computer Science · Computer Science 2023-10-12 Christian Antic

Imprecise probability is concerned with uncertainty about which probability distributions to use. It has applications in robust statistics and machine learning. We look at programming language models for imprecise probability. Our…

Programming Languages · Computer Science 2024-10-31 Jack Liell-Cock , Sam Staton

This thesis develops the translation between category theory and computational linguistics as a foundation for natural language processing. The three chapters deal with syntax, semantics and pragmatics. First, string diagrams provide a…

Computation and Language · Computer Science 2022-12-14 Giovanni de Felice

In this paper we consider the problem of unambiguous discrimination between a set of linearly independent pure quantum states. We show that the design of the optimal measurement that minimizes the probability of an inconclusive result can…

Quantum Physics · Physics 2016-11-17 Yonina C. Eldar

Synchronous languages are now a standard industry tool for critical embedded systems. Designers write high-level specifications by composing streams of values using block diagrams. These languages have been extended with Bayesian reasoning…

Programming Languages · Computer Science 2023-09-11 Guillaume Baudart , Louis Mandel , Christine Tasson
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