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Causal decomposition has provided a powerful tool to analyze health disparity problems, by assessing the proportion of disparity caused by each mediator. However, most of these methods lack \emph{policy implications}, as they fail to…

Methodology · Statistics 2023-02-21 Xinwei Sun , Xiangyu Zheng , Jim Weinstein

We compute the causality/positivity bounds on the Wilson coefficients of scalar-tensor effective field theories. Two-sided bounds are obtained by extracting IR information from UV physics via dispersion relations of scattering amplitudes,…

High Energy Physics - Theory · Physics 2023-10-24 Dong-Yu Hong , Zhuo-Hui Wang , Shuang-Yong Zhou

A novel topological and computational method for 'motion' is described. Motion is constrained by inequalities in terms of Kolmogorov Complexity. Causality is obtained as the output of a high-pass filter, passing through only high values of…

Computational Complexity · Computer Science 2012-04-26 Dara O. Shayda

Causal Bayesian networks are 'causal' models since they make predictions about interventional distributions. To connect such causal model predictions to real-world outcomes, we must determine which actions in the world correspond to which…

Machine Learning · Statistics 2025-02-04 Frederik Hytting Jørgensen , Luigi Gresele , Sebastian Weichwald

Causal models have proven extremely useful in offering formal representations of causal relationships between a set of variables. Yet in many situations, there are non-causal relationships among variables. For example, we may want variables…

Artificial Intelligence · Computer Science 2023-01-18 Sander Beckers , Joseph Y. Halpern , Christopher Hitchcock

Scattering off the edge of a composite particle or finite-range interaction can precede that off its center. An effective theory treatment with pointlike particles and contact interactions must find that the scattered experimental wave is…

High Energy Physics - Phenomenology · Physics 2021-06-07 Felipe J. Llanes-Estrada , Raul Roldan-Gonzalez

Models of particle propagation in causal set theory are investigated through simulations. For the swerves model the simulations are shown to agree with the expected continuum diffusion behaviour. Given the limitations on the simulated…

General Relativity and Quantum Cosmology · Physics 2015-05-14 Lydia Philpott

Let $M$ and $N$ be smooth closed connected aspherical manifolds with good (in the sense of Serre) fundamental groups $G$ and $H$. We show that if $\widehat G\cong \widehat H$, then $M$ and $N$ are cobordant and the signatures of $M$ and $N$…

Group Theory · Mathematics 2026-01-12 Sam Hughes , Andrew Ng

We determine the complete set of generalized spin squeezing inequalities. These are entanglement criteria that can be used for the experimental detection of entanglement in a system of spin-1/2 particles in which the spins cannot be…

Quantum Physics · Physics 2011-11-09 Geza Toth , Christian Knapp , Otfried Gühne , Hans J. Briegel

Current-induced spin torques in layered magnetic heterostructures have many commonalities across broad classes of magnetic materials. These include not only collinear ferromagnets, ferrimagnets, and antiferromagnets, but also more complex…

Mesoscale and Nanoscale Physics · Physics 2021-02-24 Yaroslav Tserkovnyak , Eran Maniv , James Analytis

This article is concerned with causal structures, which are defined as a field of tangentially non-degenerate projective hypersurfaces in the projectivized tangent bundle of a manifold. The local equivalence problem of causal structures on…

Differential Geometry · Mathematics 2018-08-07 Omid Makhmali

Existing algorithms for explaining the outputs of image classifiers are based on a variety of approaches and produce explanations that frequently lack formal rigour. On the other hand, logic-based explanations are formally and rigorously…

Artificial Intelligence · Computer Science 2026-02-20 David A Kelly , Hana Chockler

We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called…

Theoretical Economics · Economics 2024-01-23 Joseph Y. Halpern , Evan Piermont

Two multiplicative anomalies are evaluated for the determinant of the conformal higher spin propagating operator on spheres given by Tseytlin. One holds for the decomposition of the higher derivative product into its individual second order…

High Energy Physics - Theory · Physics 2015-06-11 J. S. Dowker

The expression of causality depends on an underlying choice of chronology. Since a chronology is provided by any Lorentzian metric in relativistic theories, there are as many expressions of causality as there are non-conformally related…

High Energy Physics - Theory · Physics 2007-05-23 Jean-Philippe Bruneton

Uplift modeling requires experimental data, preferably collected in random fashion. This places a logistical and financial burden upon any organisation aspiring such models. Once deployed, uplift models are subject to effects from concept…

Artificial Intelligence · Computer Science 2019-02-04 Jeroen Berrevoets , Wouter Verbeke

We propose an improved effective-medium theory to obtain the concentration dependence of the viscosity of particle suspensions at arbitrary volume fractions. Our methodology can be applied, in principle, to any particle shape as long as the…

Soft Condensed Matter · Physics 2010-06-01 I. Santamaria-Holek , Carlos I. Mendoza

This report aims to present the main ideas of Regge calculus necessary to understand the basic premise of CDT. Next, the main strategy of the CDT approach is introduced in general terms. The main focus of this report is the 2-D model of…

High Energy Physics - Theory · Physics 2011-09-20 Alex Forcier

We consider dissipative strongly competitive systems $\dot{x}_{i}=x_{i}f_{i}(x)$ of ordinary differential equations. It is known that for a wide class of such systems there exists an invariant attracting hypersurface $\Sigma$, called the…

Dynamical Systems · Mathematics 2017-08-18 Janusz Mierczyński

Causal inference is a central goal across many scientific disciplines. Over the past several decades, three major frameworks have emerged to formalize causal questions and guide their analysis: the potential outcomes framework, structural…

Statistics Theory · Mathematics 2026-02-12 Linbo Wang , Thomas Richardson , James Robins
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