English
Related papers

Related papers: Conditional Random Quantities and Compounds of Con…

200 papers

We unify the resource-theoretic and the cohomological perspective on quantum contextuality. At the center of this unification stands the notion of the contextual fraction. For both symmetry and parity based contextuality proofs, we…

Quantum Physics · Physics 2018-06-13 Cihan Okay , Emily Tyhurst , Robert Raussendorf

Improving Importance Sampling estimators for rare event probabilities requires sharp approximations of conditional densities. This is achieved for events E_{n}:=(f(X_{1})+...+f(X_{n}))\inA_{n} where the summands are i.i.d. and E_{n} is a…

Probability · Mathematics 2012-02-08 Michel Broniatowski , Virgile Caron

When considering the problem of forecasting a continuous-time stochastic process over an entire time-interval in terms of its recent past, the notion of Autoregressive Hilbert space processes (ARH) arises. This model can be seen as a…

Methodology · Statistics 2013-02-15 Jairo Cugliari

We discuss some properties of conditional expectation operators, and use these facts to prove an interesting counterexample regarding sufficient statistics. In particular, we show that there exists sufficient random variables X and Y, such…

Statistics Theory · Mathematics 2011-07-05 Andrew Tausz

Considering a minimal number of assumptions and in the context of the timeless formalism, conditional probabilities are derived for subsequent measurements in the non-relativistic regime. Only unitary transformations are considered with…

Quantum Physics · Physics 2024-01-30 Martino Trassinelli

Contextuality is a particular quantum phenomenon that has no analogue in classical probability theory. Given two independent systems, a natural question is how to represent such a situation as a single test space. In other words, how…

Quantum Physics · Physics 2018-12-24 Ana Belén Sainz , Elie Wolfe

Contextual stochastic optimization is an advanced methodology to model uncertainty in the presence of contextual information during decision planning processes. Although classical methodologies focus on minimizing the expectation of a…

Optimization and Control · Mathematics 2025-11-24 Man Yiu Tsang , Tony Sit , Hoi Ying Wong

The problem is sequence prediction in the following setting. A sequence $x_1,...,x_n,...$ of discrete-valued observations is generated according to some unknown probabilistic law (measure) $\mu$. After observing each outcome, it is required…

Artificial Intelligence · Computer Science 2012-03-20 Daniil Ryabko

If quantum mechanics is taken for granted the randomness derived from it may be vacuous or even delusional, yet sufficient for many practical purposes. "Random" quantum events are intimately related to the emergence of both space-time as…

Quantum Physics · Physics 2021-04-27 Karl Svozil

We investigate the sample complexity of mutual information and conditional mutual information testing. For conditional mutual information testing, given access to independent samples of a triple of random variables $(A, B, C)$ with unknown…

Data Structures and Algorithms · Computer Science 2025-06-05 Jan Seyfried , Sayantan Sen , Marco Tomamichel

Many causal questions involve interactions between units, also known as interference, for example between individuals in households, students in schools, or firms in markets. In this paper, we formalize the concept of a conditioning…

Methodology · Statistics 2018-09-25 Guillaume Basse , Avi Feller , Panos Toulis

In quantum mechanics, not everything that can be observed can be observed simultaneously. Observational data exhibits \emph{contextuality} -- a generalisation of nonlocality -- if the result of an observation is necessarily dependent on…

Quantum Physics · Physics 2026-03-13 Ask Ellingsen

We present a complete reasoning principle for contextual equivalence in an untyped probabilistic language. The language includes continuous (real-valued) random variables, conditionals, and scoring. It also includes recursion, since the…

Programming Languages · Computer Science 2018-07-10 Mitchell Wand , Ryan Culpepper , Theophilos Giannakopoulos , Andrew Cobb

A probabilistic propositional logic, endowed with an epistemic component for asserting (non-)compatibility of diagonizable and bounded observables, is presented and illustrated for reasoning about the random results of projective…

Logic · Mathematics 2018-03-20 A. Sernadas , J. Rasga , C. Sernadas , L. Alcácer , A. B. Henriques

The definition of conditional probability in case of continuous distributions was an important step in the development of mathematical theory of probabilities. How can we define this notion in algorithmic probability theory? In this survey…

Logic · Mathematics 2016-07-15 Bruno Bauwens , Alexander Shen , Hayato Takahashi

Most of the stochastic orders for comparing random variables, considered in the literature, are afflicted with two main drawbacks: (i) lack of connex property and (ii) lack of consideration of any dependence structure between the random…

Methodology · Statistics 2021-03-03 Sugata Ghosh , Asok K. Nanda

We present a domain-theoretic framework for probabilistic programming that provides a constructive definition of conditional probability and addresses computability challenges previously identified in the literature. We introduce a novel…

Logic in Computer Science · Computer Science 2025-02-04 Pietro Di Gianantonio , Abbas Edalat

We study the role of context, complex of physical conditions, in quantum as well as classical experiments. It is shown that by taking into account contextual dependence of experimental probabilities we can derive the quantum rule for the…

High Energy Physics - Theory · Physics 2009-11-07 Andrei Khrennikov

Contextuality, the impossibility of assigning a single random variable to represent the outcomes of the same measurement procedure under different experimental conditions, is a central aspect of quantum mechanics. Thus defined, it appears…

Neurons and Cognition · Quantitative Biology 2016-02-17 J. Acacio de Barros , Gary Oas

Conditional independence, and more generally conditional mutual independence, are central notions in probability theory. In their general forms, they include functional dependence as a special case. In this paper, we tackle two fundamental…

Probability · Mathematics 2026-03-24 Laigang Guo , Raymond W. Yeung , Tao Guo