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Due to the challenge posed by multi-source and heterogeneous data collected from diverse environments, causal relationships among features can exhibit variations influenced by different time spans, regions, or strategies. This diversity…

Machine Learning · Computer Science 2025-02-11 Lu Liu , Yang Tang , Kexuan Zhang , Qiyu Sun

Predicting tensorial properties with machine learning models typically requires carefully designed tensorial descriptors. In this work, we introduce an alternative strategy for learning tensorial quantities based on scalar descriptors. We…

Materials Science · Physics 2026-02-05 Bernhard Schmiedmayer , Angela Rittsteuer , Tobias Hilpert , Georg Kresse

We define a new type of transformation for Lorentzian manifolds characterized by mapping every causal future-directed vector onto a causal future-directed vector. The set of all such transformations, which we call causal symmetries, has the…

Mathematical Physics · Physics 2016-08-16 A. García-Parrado , J. M. M. Senovilla

Differentiable causal discovery has made significant advancements in the learning of directed acyclic graphs. However, its application to real-world datasets remains restricted due to the ubiquity of latent confounders and the requirement…

Machine Learning · Computer Science 2024-06-18 Pingchuan Ma , Rui Ding , Qiang Fu , Jiaru Zhang , Shuai Wang , Shi Han , Dongmei Zhang

Quantum mechanics allows for coherent control over the order in which different processes take place on a target system, giving rise to a new feature known as indefinite causal order. Indefinite causal order provides a resource for quantum…

It is difficult to extract reliable criteria for causal locality from the limited ingredients found in textbook quantum theory. In the end, Bell humbly warned that his eponymous theorem was based on criteria that "should be viewed with the…

Quantum Physics · Physics 2024-02-28 Jacob A. Barandes

We study the Potts model (defined geometrically in the cluster picture) on finite two-dimensional lattices of size L x N, with boundary conditions that are free in the L-direction and periodic in the N-direction. The decomposition of the…

Mathematical Physics · Physics 2007-08-30 Jean-Francois Richard , Jesper Lykke Jacobsen

Polarization phenomena are essential for the understanding of elementary processes, and are typically large in the threshold region. The selection rules with respect to P-parity, angular momentum, isotopic spin and the Pauli principle allow…

Nuclear Theory · Physics 2007-05-23 Michail P. Rekalo , Egle Tomasi-Gustafsson

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

Using dispersion relations of the scattering amplitudes and semi-definite programming, we calculate causality bounds on the Wilson coefficients in scalar-tensor effective field theories that include parity-violating operators. Particular…

High Energy Physics - Theory · Physics 2025-05-23 Hao Xu , Dong-Yu Hong , Zhuo-Hui Wang , Shuang-Yong Zhou

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

Causal discovery is a structured prediction task that aims to predict causal relations among variables based on their data samples. Supervised Causal Learning (SCL) is an emerging paradigm in this field. Existing Deep Neural Network…

Machine Learning · Computer Science 2025-02-18 Jiaru Zhang , Rui Ding , Qiang Fu , Bojun Huang , Zizhen Deng , Yang Hua , Haibing Guan , Shi Han , Dongmei Zhang

Causal inequalities are bounds on correlations obtained when operations take place in a causal sequence, i.e. in which the background time or definite causal structure pre-exists such that every operation is either in the future, in the…

Quantum Physics · Physics 2015-09-22 Caslav Brukner

Detecting and localizing change points in sequential data is of interest in many areas of application. Various notions of change points have been proposed, such as changes in mean, variance, or the linear regression coefficient. In this…

Methodology · Statistics 2024-03-20 Shimeng Huang , Jonas Peters , Niklas Pfister

General definitions for causal structures on manifolds of dimension d+1>2 are presented for the topological category and for any differentiable one. Locally, these are given as cone structures via local (pointwise) homeomorphic or…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Martin Rainer

Neurally-parameterized Structural Causal Models in the Pearlian notion to causality, referred to as NCM, were recently introduced as a step towards next-generation learning systems. However, said NCM are only concerned with the learning…

Machine Learning · Computer Science 2022-12-27 Matej Zečević , Devendra Singh Dhami , Kristian Kersting

By relating and ordering events, causality constitutes a pivotal feature of our world. On the one hand, there are information-theoretic notions of causality defined in terms of the information processing ability of agents and on the other…

Quantum Physics · Physics 2023-04-26 Maarten Grothus

Starting with the well-defined product of quantum fields at two spacetime points, we explore an associated Poisson structure for classical field theories within the deformation quantization formalism. We realize that the induced…

High Energy Physics - Theory · Physics 2016-07-13 Jasel Berra-Montiel , Alberto Molgado , César D. Palacios-García

On plain physical grounds localization of relativistic quantum particles is extended to the achronal regions of Minkowski spacetime. Achronal localization fulfills automatically the requirements of causality. It constitutes the frame which…

Mathematical Physics · Physics 2025-03-06 Domenico P. L. Castrigiano

Advances in single-cell omics allow for unprecedented insights into the transcription profiles of individual cells. When combined with large-scale perturbation screens, through which specific biological mechanisms can be targeted, these…

Machine Learning · Computer Science 2023-10-24 Alejandro Tejada-Lapuerta , Paul Bertin , Stefan Bauer , Hananeh Aliee , Yoshua Bengio , Fabian J. Theis