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Different statistical samples (e.g., from different locations) offer populations and learning systems observations with distinct statistical properties. Samples under (1) 'Unconfounded' growth preserve systems' ability to determine the…

Methodology · Statistics 2025-08-05 Andre F. Ribeiro

This work investigates whether time series of natural phenomena can be understood as being generated by sequences of latent states which are ordered in systematic and regular ways. We focus on clinical time series and ask whether clinical…

Machine Learning · Computer Science 2025-08-29 Michael Hagmann , Michael Staniek , Stefan Riezler

Causal set theory is a discrete model of spacetime that retains a notion of causal structure. We understand how to construct causal sets that approximate a given spacetime, but most causal sets are not at all manifold-like, and must be…

General Relativity and Quantum Cosmology · Physics 2023-04-12 P. Carlip , S. Carlip , S. Surya

A formulation of singular classical theories (determined by degenerate Lagrangians) without constraints is presented. A partial Hamiltonian formalism in the phase space having an initially arbitrary number of momenta (which can be smaller…

Mathematical Physics · Physics 2014-09-09 Steven Duplij

Our common understanding of the physical world deeply relies on the notion that events are ordered with respect to some time parameter, with past events serving as causes for future ones. Nonetheless, it was recently found that it is…

We consider a bivariate time series $(X_t,Y_t)$ that is given by a simple linear autoregressive model. Assuming that the equations describing each variable as a linear combination of past values are considered structural equations, there is…

Statistics Theory · Mathematics 2018-04-12 Dominik Janzing , Paul Rubenstein , Bernhard Schölkopf

Robust causal discovery from observational data under imperfect prior knowledge remains a significant and largely unresolved challenge. Existing methods typically presuppose perfect priors or can only handle specific, pre-identified error…

Machine Learning · Computer Science 2025-11-11 Zidong Wang , Xi Lin , Chuchao He , Xiaoguang Gao

A unifying framework for the study of causal relations is presented. The causal relations are regarded as subsets of M x M and the role of the corresponding antisymmetry conditions in the construction of the causal ladder is stressed. The…

General Relativity and Quantum Cosmology · Physics 2011-07-08 E. Minguzzi

We introduce and study a non uniform hyperbolicity condition for complex rational maps, that does not involve a growth condition. We call this condition Backward Contraction. We show this condition is weaker than the Collet-Eckmann…

Dynamical Systems · Mathematics 2007-05-23 Juan Rivera-Letelier

Treating the time of an event as a quantum variable, we derive a scheme in which superpositions in time are used to perform operations in an indefinite causal order. We use some aspects of a recently developed space-time-symmetric formalism…

Quantum Physics · Physics 2022-07-13 David Felce , Nicetu Tibau Vidal , Vlatko Vedral , Eduardo O. Dias

A new delay equation is introduced to describe the punctuated evolution of complex nonlinear systems. A detailed analytical and numerical investigation provides the classification of all possible types of solutions for the dynamics of a…

Adaptation and Self-Organizing Systems · Physics 2015-05-13 V. I. Yukalov , E. P. Yukalova , D. Sornette

The capability of imagining internally with a mental model of the world is vitally important for human cognition. If a machine intelligent agent can learn a world model to create a "dream" environment, it can then internally ask what-if…

Machine Learning · Computer Science 2020-12-29 Minne Li , Mengyue Yang , Furui Liu , Xu Chen , Zhitang Chen , Jun Wang

We consider the usual causal structure $(I^+,J^+)$ on a spacetime, and a number of alternatives based on Minguzzi's $D^+$ and Sorkin and Woolgar's $K^+$, in the case where the spacetime metric is continuous, but not necessarily smooth. We…

General Relativity and Quantum Cosmology · Physics 2021-06-30 Leonardo García-Heveling

It is commonplace to encounter nonstationary data, of which the underlying generating process may change over time or across domains. The nonstationarity presents both challenges and opportunities for causal discovery. In this paper we…

Artificial Intelligence · Computer Science 2016-06-21 Kun Zhang , Biwei Huang , Jiji Zhang , Bernhard Schölkopf , Clark Glymour

We construct a stochastic dynamical systems theory in which sustainability is a structural boundary property of a fully coupled Earth--Human--Production system. Each subsystem is modelled as a vector-valued process governed by stochastic…

Theoretical Economics · Economics 2026-03-02 Claudio Pirrone , Stefano Fricano , Gioacchino Fazio

We demonstrate the breakdown of several fundamentals of Lorentzian causality theory in low regularity. Most notably, chronological futures (defined naturally using locally Lipschitz curves) may be non-open, and may differ from the…

Differential Geometry · Mathematics 2021-06-15 James D. E. Grant , Michael Kunzinger , Clemens Sämann , Roland Steinbauer

Quantum causal histories are defined to be causal sets with Hilbert spaces attached to each event and local unitary evolution operators. The reflexivity, antisymmetry, and transitivity properties of a causal set are preserved in the quantum…

High Energy Physics - Theory · Physics 2009-10-31 Fotini Markopoulou

Unmeasured causal forces influence diverse experimental time series, such as the transcription factors that regulate genes, or the descending neurons that steer motor circuits. Combining the theory of skew-product dynamical systems with…

Machine Learning · Computer Science 2024-12-03 William Gilpin

This paper examines the conceptual convergence between Lee Smolin's Causal Theory of Views, Karl Friston's Free Energy Principle, and contemporary psychological accounts of the functions of consciousness. Although formulated within…

Physics and Society · Physics 2026-02-18 Anna Sverdlik

Geometry of networks endowed with a causal structure is discussed using the conventional framework of equilibrium statistical mechanics. The popular growing network models appear as particular causal models. We focus on a class of tree…

Statistical Mechanics · Physics 2009-11-07 P. Bialas , Z. Burda , J. Jurkiewicz , A. Krzywicki
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