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Computational context understanding refers to an agent's ability to fuse disparate sources of information for decision-making and is, therefore, generally regarded as a prerequisite for sophisticated machine reasoning capabilities, such as…

Artificial Intelligence · Computer Science 2020-03-11 Alessandro Oltramari , Jonathan Francis , Cory Henson , Kaixin Ma , Ruwan Wickramarachchi

We show that the phenomenon of quantum contextuality can be used to certify lower bounds on the dimension accessed by the measurement devices. To prove this, we derive bounds for different dimensions and scenarios of the simplest…

Quantum Physics · Physics 2014-06-12 Otfried Gühne , Costantino Budroni , Adan Cabello , Matthias Kleinmann , Jan-Åke Larsson

We tackle the problem of conditioning probabilistic programs on distributions of observable variables. Probabilistic programs are usually conditioned on samples from the joint data distribution, which we refer to as deterministic…

Machine Learning · Computer Science 2021-03-09 David Tolpin , Yuan Zhou , Tom Rainforth , Hongseok Yang

We employ the resource theory of generalized contextuality as a tool for analyzing the structure of prepare-and-measure scenarios. We argue that this framework simplifies proofs of quantum contextuality in complex scenarios and strengthens…

Quantum Physics · Physics 2023-11-29 Rafael Wagner , Roberto D. Baldijão , Alisson Tezzin , Bárbara Amaral

The Kochen-Specker theorem demonstrates that it is not possible to reproduce the predictions of quantum theory in terms of a hidden variable model where the hidden variables assign a value to every projector deterministically and…

Quantum Physics · Physics 2015-09-16 Ravi Kunjwal , Robert W. Spekkens

Standard quantum mechanics undeniably violates the notion of separability that classical physics accustomed us to consider as valid. By relating the phenomenon of quantum nonseparability to the all-important concept of potentiality, we…

Quantum Physics · Physics 2008-11-25 Vassilios Karakostas

Causal structure learning with data from multiple contexts carries both opportunities and challenges. Opportunities arise from considering shared and context-specific causal graphs enabling to generalize and transfer causal knowledge across…

Machine Learning · Computer Science 2024-10-29 Martin Rabel , Wiebke Günther , Jakob Runge , Andreas Gerhardus

There is significant evidence that real-world communication cannot be reduced to sending signals with context-independent meaning. In this work, based on a variant of the classical Lewis (1969) signaling model, we explore the conditions for…

Artificial Intelligence · Computer Science 2024-08-06 Krzysztof Główka , Julian Zubek , Joanna Rączaszek-Leonardi

Quantum contextuality is one of the most perplexing and peculiar features of quantum mechanics. Concisely, it refers to the observation that the result of a single measurement in quantum mechanics depends on the set of joint measurements…

Quantum Physics · Physics 2022-10-28 Zheng-Hao Liu , Qiang Li , Bi-Heng Liu , Yun-Feng Huang , Jin-Shi Xu , Chuan-Feng Li , Guang-Can Guo

The Contextuality-by-Default approach to determining and measuring the (non)contextuality of a system of random variables requires that every random variable in the system be represented by an equivalent set of dichotomous random variables.…

Quantum Physics · Physics 2022-01-05 Janne V. Kujala , Ehtibar N. Dzhafarov

Quantum contextuality is the key concept which explains the fact that the result of a measurement is not independent of the context in which it is found. It is observed to be an intrinsic feature, i.e., neither entanglement nor spatial…

Quantum Physics · Physics 2023-02-23 Firat Diker , Zafer Gedik

We introduce contextual values as a generalization of the eigenvalues of an observable that takes into account both the system observable and a general measurement procedure. This technique leads to a natural definition of a general…

Quantum Physics · Physics 2010-06-16 J. Dressel , S. Agarwal , A. N. Jordan

Many probabilistic programming languages allow programs to be run under constraints in order to carry out Bayesian inference. Running programs under constraints could enable other uses such as rare event simulation and probabilistic…

Programming Languages · Computer Science 2015-01-19 Neil Toronto , Jay McCarthy , David Van Horn

Finding a set of empirical criteria fulfilled by any theory satisfying the generalized notion of noncontextuality is a challenging task of both operational and foundational importance. This work presents a methodology for constructing the…

Quantum Physics · Physics 2026-05-04 Soumyabrata Hazra , Debashis Saha , Anubhav Chaturvedi , Subhankar Bera , A. S. Majumdar

Probabilistic program analysis aims to quantify the probability that a given program satisfies a required property. It has many potential applications, from program understanding and debugging to computing program reliability, compiler…

Programming Languages · Computer Science 2017-09-08 Aleksandar S. Dimovski

Probabilistic context-free grammars have a long-term record of use as generative models in machine learning and symbolic regression. When used for symbolic regression, they generate algebraic expressions. We define the latter as equivalence…

Formal Languages and Automata Theory · Computer Science 2022-12-05 Urh Primožič , Ljupčo Todorovski , Matej Petković

One can often encounter claims that classical (Kolmogorovian) probability theory cannot handle, or even is contradicted by, certain empirical findings or substantive theories. This note joins several previous attempts to explain that these…

Probability · Mathematics 2019-01-24 Ehtibar N. Dzhafarov , Maria Kon

Quantum measurements are noncontextual, with outcomes independent of which other commuting observables are measured at the same time, when consistently analyzed using principles of Hilbert space quantum mechanics rather than classical…

Quantum Physics · Physics 2013-06-06 Robert B. Griffiths

By analyzing the concept of contextuality (Bell-Kochen-Specker) in terms of pre-and-post-selection (PPS), it is possible to assign definite values to observables in a new and surprising way. Physical reasons are presented for restrictions…

Quantum Physics · Physics 2009-11-13 Jeff Tollaksen

Generating realistic images from scene graphs asks neural networks to be able to reason about object relationships and compositionality. As a relatively new task, how to properly ensure the generated images comply with scene graphs or how…

Computer Vision and Pattern Recognition · Computer Science 2019-01-17 Subarna Tripathi , Anahita Bhiwandiwalla , Alexei Bastidas , Hanlin Tang
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