English
Related papers

Related papers: Extending the fair sampling assumption using causa…

200 papers

We present a loophole-free violation of local realism using entangled photon pairs. We ensure that all relevant events in our Bell test are spacelike separated by placing the parties far enough apart and by using fast random number…

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate distortion theory to use causal shielding---a natural principle of learning. We study two distinct cases of causal inference:…

Information Theory · Computer Science 2010-08-23 Susanne Still , James P. Crutchfield , Christopher J. Ellison

This paper uses anthropic reasoning to argue for a reduced likelihood that superintelligent AI will come into existence in the future. To make this argument, a new principle is introduced: the Super-Strong Self-Sampling Assumption (SSSSA),…

Artificial Intelligence · Computer Science 2017-05-10 Toby Pereira

A locally causal hidden-variable theory of quantum physics need not be constrained by the Bell inequalities if this theory also partially violates the measurement independence condition. However, such violation can appear unphysical,…

Quantum Physics · Physics 2015-02-26 T. N. Palmer

Contextuality and entanglement are valuable resources for quantum computing and quantum information. Bell inequalities are used to certify entanglement; thus, it is important to understand why and how they are violated. Quantum mechanics…

Quantum Physics · Physics 2021-08-30 Marian Kupczynski

Over the past few decades, addressing "spatial confounding" has become a major topic in spatial statistics. However, the literature has provided conflicting definitions, and many proposed solutions are tied to specific analysis models and…

Methodology · Statistics 2024-10-14 Brian Gilbert , Abhirup Datta , Joan A. Casey , Elizabeth L. Ogburn

Recent theoretical work in causal inference has explored an important class of variables which, when conditioned on, may further amplify existing unmeasured confounding bias (bias amplification). Despite this theoretical work, existing…

Methodology · Statistics 2020-03-20 Tyrel Stokes , Russell Steele , Ian Shrier

The estimation of an f-divergence between two probability distributions based on samples is a fundamental problem in statistics and machine learning. Most works study this problem under very weak assumptions, in which case it is provably…

Machine Learning · Statistics 2019-10-25 Paul K. Rubenstein , Olivier Bousquet , Josip Djolonga , Carlos Riquelme , Ilya Tolstikhin

It is a recent realization that many of the concepts and tools of causal discovery in machine learning are highly relevant to problems in quantum information, in particular quantum nonlocality. The crucial ingredient in the connection…

Quantum Physics · Physics 2016-01-11 Rafael Chaves

In this paper we propose a causal modeling approach to intersectional fairness, and a flexible, task-specific method for computing intersectionally fair rankings. Rankings are used in many contexts, ranging from Web search results to…

Machine Learning · Computer Science 2020-06-17 Ke Yang , Joshua R. Loftus , Julia Stoyanovich

Structural causal models are the basic modelling unit in Pearl's causal theory; in principle they allow us to solve counterfactuals, which are at the top rung of the ladder of causation. But they often contain latent variables that limit…

Artificial Intelligence · Computer Science 2021-11-23 Marco Zaffalon , Alessandro Antonucci , Rafael Cabañas

Experimental violations of Bell inequalities are in general vulnerable to so-called "loopholes." In this work, we analyse the characteristics of a loophole-free Bell test with photons, closing simultaneously the locality, freedom-of-choice,…

Quantum Physics · Physics 2016-03-11 Johannes Kofler , Marissa Giustina , Jan-Åke Larsson , Morgan W. Mitchell

The no-signalling principle is a fundamental assumption in Bell-inequality and quantum-steering experiments. Nonetheless, experimental imperfections can lead to apparent violations beyond those expected from finite-sample statistics. Here,…

Fractionally supervised classification (FSC) offers a flexible framework for combining labeled and unlabeled data in model-based classification, but existing formulations assume simple random sampling. In many applications, however, the…

Methodology · Statistics 2026-04-29 Mohammad Jafari Jozani , Jingyu Wang

Two new formulations of Bell's theorem are given here. First, we consider a definite set of two entangled photons with only two polarization directions, for which Bell's locality assumption is violated for the case of perfect correlation.…

Quantum Physics · Physics 2007-05-23 Afshin Shafiee , Mehdi Golshani

Bipartite experiments arise in various fields, in which the treatments are randomized over one set of units, while the outcomes are measured over another separate set of units. However, existing methods often rely on strong model…

Methodology · Statistics 2025-04-16 Sizhu Lu , Lei Shi , Yue Fang , Wenxin Zhang , Peng Ding

Bell scenarios are multipartite scenarios that exclude any communication between parties. This constraint leads to a strict hierarchy of correlation sets in such scenarios, namely, classical, quantum, and nonsignaling. However, without any…

Quantum Physics · Physics 2026-05-29 Ravi Kunjwal , Ognyan Oreshkov

The presence of Bell-nonlocality in the correlations arising from measuring spatially-separated systems guarantees that the sets of measurements used are necessarily incompatible. Not all sets of incompatible measurements can however lead…

Quantum Physics · Physics 2025-08-21 Andrés F. Ducuara , Patryk Lipka-Bartosik , Cristian E. Susa , Paul Skrzypczyk

This article provides a comprehensive review of the critical role of detection efficiency in demonstrating non-classicality across various device-independent and semi-device-independent scenarios. The central focus is the detection…

A fundamental question in causal inference is whether it is possible to reliably infer manipulation effects from observational data. There are a variety of senses of asymptotic reliability in the statistical literature, among which the most…

Artificial Intelligence · Computer Science 2012-12-12 Jiji Zhang , Peter L. Spirtes