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It has recently been found that Bell scenarios are only a small subclass of interesting setups for studying the non-classical features of quantum theory within spacetime. We find that it is possible to talk about classical correlations,…

Quantum Physics · Physics 2016-01-12 Tobias Fritz

The landscape of causal relations that can hold among a set of systems in quantum theory is richer than in classical physics. In particular, a pair of time-ordered systems can be related as cause and effect or as the effects of a common…

Quantum Physics · Physics 2017-07-20 Katja Ried , Jean-Philippe W. MacLean , Robert W. Spekkens , Kevin J. Resch

In this article we propose an extension to the typed natural deduction calculus TNDPQ to model verification of individual fairness and intersectionality in probabilistic classifiers. Their interpretation is obtained by formulating specific…

Logic in Computer Science · Computer Science 2025-10-28 Leonardo Ceragioli , Giuseppe Primiero

Certain causal models involving unmeasured variables induce no independence constraints among the observed variables but imply, nevertheless, inequality contraints on the observed distribution. This paper derives a general formula for such…

Artificial Intelligence · Computer Science 2013-02-21 Judea Pearl

The problem of characterizing classical and quantum correlations in networks is considered. Contrary to the usual Bell scenario, where distant observers share a physical system emitted by one common source, a network features several…

Quantum Physics · Physics 2021-04-21 Armin Tavakoli , Marc-Olivier Renou , Nicolas Gisin , Nicolas Brunner

Causal representation learning aims to unveil latent high-level causal representations from observed low-level data. One of its primary tasks is to provide reliable assurance of identifying these latent causal models, known as…

Machine Learning · Computer Science 2024-12-02 Yuhang Liu , Zhen Zhang , Dong Gong , Mingming Gong , Biwei Huang , Anton van den Hengel , Kun Zhang , Javen Qinfeng Shi

Classical machine learning models struggle with learning and prediction tasks on data sets exhibiting long-range correlations. Previously, the existence of a long-range correlational structure known as contextuality was shown to inhibit…

Quantum Physics · Physics 2026-04-28 Mariesa H. Teo , Willers Yang , James Sud , Teague Tomesh , Frederic T. Chong , Eric R. Anschuetz

We study constrained versions of the Ingleton inequality in the entropic setting and quantify its stability under small violations of conditional independence. Although the classical Ingleton inequality fails for general entropy profiles,…

Information Theory · Computer Science 2026-03-24 Rostislav Matveev , Andrei Romashchenko

Entanglement witnesses such as Bell inequalities are frequently used to prove the non-classicality of a light source and its suitability for further tasks. By demonstrating Bell inequality violations using classical light in common…

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

Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focus on uncovering causal structures among observed…

Machine Learning · Computer Science 2026-03-03 Songyao Jin , Biwei Huang

Qualitative causal relationships compactly express the direction, dependency, temporal constraints, and monotonicity constraints of discrete or continuous interactions in the world. In everyday or academic language, we may express…

Machine Learning · Computer Science 2021-08-31 Scott E. Friedman , Ian H. Magnusson , Sonja M. Schmer-Galunder

We develop estimation for potentially high-dimensional additive structural equation models. A key component of our approach is to decouple order search among the variables from feature or edge selection in a directed acyclic graph encoding…

Methodology · Statistics 2014-12-02 Peter Bühlmann , Jonas Peters , Jan Ernest

We introduce an approach which allows detecting causal relationships between variables for which the time evolution is available. Causality is assessed by a variational scheme based on the Information Imbalance of distance ranks, a…

Methodology · Statistics 2024-05-07 Vittorio Del Tatto , Gianfranco Fortunato , Domenica Bueti , Alessandro Laio

We study causal inference in a multi-environment setting, in which the functional relations for producing the variables from their direct causes remain the same across environments, while the distribution of exogenous noises may vary. We…

Machine Learning · Computer Science 2017-05-29 AmirEmad Ghassami , Saber Salehkaleybar , Negar Kiyavash , Kun Zhang

What types of differences among causal structures with latent variables are impossible to distinguish by statistical data obtained by probing each visible variable? If the probing scheme is simply passive observation, then it is well-known…

Machine Learning · Statistics 2024-07-03 Marina Maciel Ansanelli , Elie Wolfe , Robert W. Spekkens

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports…

Methodology · Statistics 2024-12-31 Matias Janvin , Jessica G. Young , Pål C. Ryalen , Mats J. Stensrud

Recently ({\em Class. Quant. Grav.} {\bf 20} 625-664) the concept of {\em causal mapping} between spacetimes --essentially equivalent in this context to the {\em chronological map} one in abstract chronological spaces--, and the related…

Mathematical Physics · Physics 2021-05-25 Alfonso García-Parrado , Miguel Sánchez

Quantum theory features several phenomena which can be considered as resources for information processing tasks. Some of these effects, such as entanglement, arise in a nonlocal scenario, where a quantum state is distributed between…

Quantum Physics · Physics 2024-07-22 Martin Plávala , Otfried Gühne

Large language models (LLMs) are trained on enormous amounts of data and encode knowledge in their parameters. We propose a pipeline to elicit causal relationships from LLMs. Specifically, (i) we sample many documents from LLMs on a given…

Machine Learning · Computer Science 2026-03-05 Takashi Kameyama , Masahiro Kato , Yasuko Hio , Yasushi Takano , Naoto Minakawa