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We propose an alternative to $k$-nearest neighbors for functional data whereby the approximating neighboring curves are piecewise functions built from a functional sample. Using a locally defined distance function that satisfies…

Methodology · Statistics 2021-06-02 Antonio Elías , Raúl Jiménez , Joe Yukich

We propose a new method of discovering causal structures, based on the detection of local, spontaneous changes in the underlying data-generating model. We analyze the classes of structures that are equivalent relative to a stream of…

Artificial Intelligence · Computer Science 2013-01-14 Jin Tian , Judea Pearl

We show that families of Instantaneous Quantum Polynomial (IQP) circuits corresponding to nontrivial Bell tests exhibit nonlocality. However, we also prove that this nonlocality can only be demonstrated using post-selection or nonlinear…

Quantum Physics · Physics 2014-12-16 Joel J. Wallman , Emily Adlam

We propose a new test of local realism based on correlation measurements of continuum valued functions of positions and momenta, known as modular variables. The Wigner representation of these observables are bounded in phase space, and…

Quantum Physics · Physics 2015-12-10 Atul S. Arora , Ali Asadian

The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known…

Machine Learning · Computer Science 2023-04-11 Shuai Li , Ziqi Chen , Hongtu Zhu , Christina Dan Wang , Wang Wen

Causal discovery methods seek to identify causal relations between random variables from purely observational data, as opposed to actively collected experimental data where an experimenter intervenes on a subset of correlates. One of the…

Machine Learning · Computer Science 2021-02-08 Samir Wadhwa , Roy Dong

The following document presents some novel numerical methods valid for one and several variables, which using the fractional derivative, allow to find solutions for some non-linear systems in the complex space using real initial conditions.…

Numerical Analysis · Mathematics 2024-04-25 A. Torres-Hernandez , F. Brambila-Paz

Calibration of large-scale differential equation models to observational or experimental data is a widespread challenge throughout applied sciences and engineering. A crucial bottleneck in state-of-the art calibration methods is the…

Optimization and Control · Mathematics 2021-02-23 Jon Cockayne , Andrew B. Duncan

We propose a new inference framework called localized conformal prediction. It generalizes the framework of conformal prediction by offering a single-test-sample adaptive construction that emphasizes a local region around this test sample,…

Statistics Theory · Mathematics 2022-03-02 Leying Guan

In this paper the generalisation of previous author's formulation of fractional continuum mechanics to the case of anisotropic non-locality is presented. The considerations include the review of competitive formulations available in…

Mathematical Physics · Physics 2023-08-03 Wojciech Sumelka

We analyze quantum measurement and entanglement by solving the dynamics of stochastic amplitudes that propagate both forward and backward in time. The model allows simulation of Einstein-Podolsky-Rosen and Bell correlations, and reveals…

Quantum Physics · Physics 2024-12-13 M. D. Reid , P. D. Drummond

A new bivariate partial sum process for locally stationary time series is introduced and its weak convergence to a Brownian sheet is established. This construction enables the development of a novel self-normalized CUSUM test statistic for…

Statistics Theory · Mathematics 2026-04-15 Florian Heinrichs

Bell's theorem, stating that quantum predictions are incompatible with a local hidden variable description, is a cornerstone of quantum theory and at the center of many quantum information processing protocols. Over the years, different…

Quantum Physics · Physics 2020-05-27 I. S. Eliëns , S. G. A. Brito , R. Chaves

Computational analysis of time-course data with an underlying causal structure is needed in a variety of domains, including neural spike trains, stock price movements, and gene expression levels. However, it can be challenging to determine…

Artificial Intelligence · Computer Science 2012-05-14 Samantha Kleinberg , Bud Mishra

Many classical algorithms output graphical representations of causal structures by testing conditional independence among a set of random variables. In dynamical systems, local independence can be used analogously as a testable implication…

Other Statistics · Statistics 2020-09-14 Søren Wengel Mogensen

We introduce a general notion of fractional (noninteger) derivative for functions defined on arbitrary time scales. The basic tools for the time-scale fractional calculus (fractional differentiation and fractional integration) are then…

Classical Analysis and ODEs · Mathematics 2014-12-05 Nadia Benkhettou , Artur M. C. Brito da Cruz , Delfim F. M. Torres

In this work the implicit function theorem is used for searching local symbolic resolution of differential equations. General results of existence for first order equations are proven and some examples, one relative to cavitation in a…

Numerical Analysis · Mathematics 2025-10-20 Gianluca Argentini

The problem of using observed correlations to infer causal relations is relevant to a wide variety of scientific disciplines. Yet given correlations between just two classical variables, it is impossible to determine whether they arose from…

The intrinsic random nature of quantum physics offers novel tools for the generation of random numbers, a central challenge for a plethora of fields. Bell non-local correlations obtained by measurements on entangled states allow for the…

The paper develops a version of modal logic that stays completely within the framework provided by quantum principles, and then proves, within the framework of quantum thinking, and in particular without invoking "hidden variables", a…

Quantum Physics · Physics 2007-05-23 Henry P. Stapp