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Contextual equivalence equate terms that have the same observable behaviour in any context. A standard contextual equivalence for CCS is the strong barbed congruence. Configuration structures are a denotational semantics for processes in…

Logic in Computer Science · Computer Science 2015-11-19 Clément Aubert , Ioana Cristescu

Contextuality, a key resource for quantum advantage, describes systems in which the outcome of a measurement is not independent of other compatible measurements, in contrast to classical hidden-variable descriptions. We investigate the…

Quantum Physics · Physics 2025-12-08 Caroline Lima , María Rosa Preciado-Rivas , Sanchit Srivastava

We propose a novel approach for modeling semantic contextual relationships in videos. This graph-based model enables the learning and propagation of higher-level spatial-temporal contexts to facilitate the semantic labeling of local…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Tinghuai Wang , Huiling Wang

Recent years have seen new general notions of contextuality emerge. Most of these employ context-independent symbols to represent random variables in different contexts. As an example, the operational theory of Spekkens [1] treats an…

Quantum Physics · Physics 2020-11-16 Mojtaba Aliakbarzadeh , Kirsty Kitto

An operational definition of contextuality is introduced which generalizes the standard notion in three ways: (1) it applies to arbitrary operational theories rather than just quantum theory, (2) it applies to arbitrary experimental…

Quantum Physics · Physics 2016-09-08 R. W. Spekkens

So far, most of the literature on (quantum) contextuality and the Kochen-Specker theorem seems either to concern particular examples of contextuality, or be considered as quantum logic. Here, we develop a general formalism for contextuality…

Quantum Physics · Physics 2015-02-10 Antonio Acín , Tobias Fritz , Anthony Leverrier , Ana Belén Sainz

In a recent article entitled "A simple explanation of the quantum violation of a fundamental inequality," Cabello proposes a condition on a class of probabilistic models that, he claims, gives the same bound on contextuality for the KCBS…

Quantum Physics · Physics 2012-10-25 Joe Henson

Real-world applications of contextual bandits often exhibit non-stationarity due to seasonality, serendipity, and evolving social trends. While a number of non-stationary contextual bandit learning algorithms have been proposed in the…

Machine Learning · Computer Science 2023-10-17 Zheqing Zhu , Yueyang Liu , Xu Kuang , Benjamin Van Roy

We describe a mathematical language for determining all possible patterns of contextuality in the dependence of stochastic outputs of a system on its deterministic inputs. The central notion is that of all possible couplings for…

Mathematical Physics · Physics 2015-01-27 Ehtibar N. Dzhafarov , Janne V. Kujala

Contextuality is a fundamental feature of quantum theory and is necessary for quantum computation and communication. Serious steps have therefore been taken towards a formal framework for contextuality as an operational resource. However,…

Quantum Physics · Physics 2018-04-26 Barbara Amaral , Adán Cabello , Marcelo Terra Cunha , Leandro Aolita

Causal discovery is at the core of human cognition. It enables us to reason about the environment and make counterfactual predictions about unseen scenarios that can vastly differ from our previous experiences. We consider the task of…

Machine Learning · Computer Science 2020-12-01 Yunzhu Li , Antonio Torralba , Animashree Anandkumar , Dieter Fox , Animesh Garg

We present a detailed motivation for and definition of the contextual values of an observable, which were introduced by Dressel et al. [Phys. Rev. Lett. 104 240401 (2010)]. The theory of contextual values extends the well-established theory…

Quantum Physics · Physics 2012-02-29 J. Dressel , A. N. Jordan

The Contextuality-by-Default theory is illustrated on contextuality analysis of the idealized double-slit experiment. The experiment is described by a system of contextually labeled binary random variables each of which answers the…

Quantum Physics · Physics 2019-01-24 Ehtibar N. Dzhafarov , Janne V. Kujala

With state-of-the-art models achieving high performance on standard benchmarks, contemporary research paradigms continue to emphasize general intelligence as an enduring objective. However, this pursuit overlooks the fundamental disparities…

Artificial Intelligence · Computer Science 2023-10-03 Nick DiSanto

We propose a principle for exploring context in machine learning models. Starting with a simple assumption that each observation may or may not depend on its context, a conditional probability distribution is decomposed into two parts:…

Machine Learning · Computer Science 2019-01-23 Yun Zeng

In a recent work, it was shown by one of us (EGC) that Bell-Kochen-Specker inequality violations in phenomena satisfying the no-disturbance condition (a generalisation of the no-signalling condition) cannot in general be explained with a…

Quantum Physics · Physics 2021-08-11 J. C. Pearl , E. G. Cavalcanti

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

Logic of Behaviour in Context (LBC) is a spatio-temporal logic for expressing properties of continuous-state processes, such as biochemical reaction networks. LBC builds on the existing Metric Interval Temporal Logic (MITL) and adds a…

Logic in Computer Science · Computer Science 2017-02-13 Christopher J. Banks , Ian Stark

Clustered sampling is prevalent in empirical regression discontinuity (RD) designs, but it has not received much attention in the theoretical literature. In this paper, we introduce a general model-based framework for such settings and…

Econometrics · Economics 2026-03-20 Claudia Noack , Tomasz Olma , Christoph Rothe

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
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