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Validating and controlling safety-critical systems in uncertain environments necessitates probabilistic reachable sets of future state evolutions. The existing methods of computing probabilistic reachable sets normally assume that…

Systems and Control · Electrical Eng. & Systems 2025-02-03 Xun Shen , Ye Wang , Kazumune Hashimoto , Yuhu Wu , Sebastien Gros

Attempts to replicate probabilistic reasoning in expert systems have typically overlooked a critical ingredient of that process. Probabilistic analysis typically requires extensive judgments regarding interdependencies among hypotheses and…

Artificial Intelligence · Computer Science 2013-04-15 Marvin S. Cohen

Contextuality is central to both the foundations of quantum theory and to the novel information processing tasks. Although it was recognized before Bell's nonlocality, despite some recent proposals, it still faces a fundamental problem: how…

Quantum Physics · Physics 2014-04-02 A. Grudka , K. Horodecki , M. Horodecki , P. Horodecki , R. Horodecki , P. Joshi , W. Kłobus , A. Wójcik

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

The concepts of variability and uncertainty, both epistemic and alleatory, came from experience and coexist with different connotations. Therefore this article attempts to express their relation by analytic means firstly setting sights on…

Other Statistics · Statistics 2013-01-15 Kalman Ziha

The average result of a weak measurement of some observable $A$ can, under post-selection of the measured quantum system, exceed the largest eigenvalue of $A$. The nature of weak measurements, as well as the presence of post-selection and…

Quantum Physics · Physics 2014-11-13 Matthew F. Pusey

Recently a new impulse has been given to the experimental investigation of contextuality. In this paper we show that for a widely used definition of contextuality there can be no decisive experiment on the existence of contextuality. To…

Quantum Physics · Physics 2011-09-21 Ronnie Hermens

Prediction of events is the challenge in many different disciplines, from meteorology to finance; the more this task is difficult, the more a system is {\it complex}. Nevertheless, even according to this restricted definition, a general…

chao-dyn · Physics 2007-05-23 Maurizio Serva

As physics searches for invariants in observations, this paper looks for invariants of probabilistic observation without assuming physical structure. Structure emerges from the basic assumption of science that new information shall lead to…

Quantum Physics · Physics 2007-05-23 Johann Summhammer

Contextuality is one way of capturing the non-classicality of quantum theory. The contextual nature of a theory is often witnessed via the violation of non-contextuality inequalities---certain linear inequalities involving probabilities of…

Quantum Physics · Physics 2020-07-08 Kishor Bharti , Atul Singh Arora , Leong Chuan Kwek , Jérémie Roland

We study the contextuality of a three-level quantum system using classical conditional entropy of measurement outcomes. First, we analytically construct the minimal configuration of measurements required to reveal contextuality. Next, an…

Quantum Physics · Physics 2013-05-30 Pawel Kurzynski , Ravishankar Ramanathan , Dagomir Kaszlikowski

In a recent paper Basieva, Cervantes, Dzhafarov, and Khrennikov (2019) presented a series of experiments which they claimed show evidence for contextuality in human judgments. This was based on a set of modified Bell-like inequalities…

Neurons and Cognition · Quantitative Biology 2019-10-14 James M Yearsley , Jonathan J Halliwell

This paper introduces the concept of random context representations for the transition probabilities of a finite-alphabet stochastic process. Processes with these representations generalize context tree processes (a.k.a. variable length…

Probability · Mathematics 2016-12-09 Roberto Imbuzeiro Oliveira

This paper proposes strategies for designing a system whose computational model is subject to aleatory and epistemic uncertainty. Aleatory variables, which are caused by randomness in physical parameters, are draws from a possibly unknown…

Methodology · Statistics 2026-02-18 Luis G. Crespo

Deep neural networks often fail catastrophically by relying on spurious correlations. Most prior work assumes a clear dichotomy into spurious and reliable features; however, this is often unrealistic. For example, most of the time we do not…

Machine Learning · Computer Science 2023-07-20 Gaurav Ghosal , Amrith Setlur , Daniel S. Brown , Anca D. Dragan , Aditi Raghunathan

We present a new and feasible test proving quantum contextuality in four-dimensional Hiltbert space. In our scheme, a contradiction between quantum mechanics and noncontextual hidden variables is revealed through the measurement statistics…

Quantum Physics · Physics 2008-06-27 Yoshihiro Nambu

I assess various proposals for the source of the intuition that there is something problematic about contextuality, ultimately concluding that contextuality is best thought of in terms of fine-tuning. I then argue that as with other…

Quantum Physics · Physics 2021-11-24 Emily Adlam

Results of measurements give legitimacy to a physical theory. What if acquiring these results in the first place necessitates what the same theory considers to be an interaction? In this note, we assume that theories account for…

Quantum Physics · Physics 2019-05-01 Arne Hansen , Stefan Wolf

We present a proof for a conjecture previously formulated by Dzhafarov, Kujala, and Larsson (Foundations of Physics, in press, arXiv:1411.2244). The conjecture specifies a measure for the degree of contextuality and a criterion (necessary…

Quantum Physics · Physics 2019-09-16 Janne V. Kujala , Ehtibar N. Dzhafarov

Uncertainty representation and quantification are paramount in machine learning and constitute an important prerequisite for safety-critical applications. In this paper, we propose novel measures for the quantification of aleatoric and…

Machine Learning · Computer Science 2024-04-22 Paul Hofman , Yusuf Sale , Eyke Hüllermeier