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A class of parametric functions formed by alternating compositions of multivariate polynomials and rectification style monomial maps is studied (the layer-wise exponents are treated as fixed hyperparameters and are not optimized). For this…

Optimization and Control · Mathematics 2026-02-13 Shravan Mohan

In this article we review classical and recent results in anomalous diffusion and provide mechanisms useful for the study of the fundamentals of certain processes, mainly in condensed matter physics, chemistry and biology. Emphasis will be…

Statistical Mechanics · Physics 2019-02-25 Fernando A. Oliveira , Rogelma M. S. Ferreira , Luciano C. Lapas , Mendeli H. Vainstein

The present work pursues the aim to draw attention to unique possibilities of the skew-symmetric differential forms. At present the theory of skew-symmetric exterior differential forms that possess invariant properties has been developed.…

General Mathematics · Mathematics 2007-05-23 L. I. Petrova

Consider an n by n matrix x_ij, and consider the quantity || x_{i,pi(i)} ||_X where X is a symmetric sequence space as a random variable where the permutation pi is chosen randomly. This was considered by Kwapien and Schutt, and we extend…

Functional Analysis · Mathematics 2008-02-03 Evgueni M. Semenov , Stephen J. Montgomery-Smith

The infinite (in both directions) sequence of the distributions $\mu^{(k)}$ of the stochastic integrals $\int_0^{\infty-}c^{-N_{t-}^{(k)}} dL_t^{(k)}$ for integers $k$ is investigated. Here $c>1$ and $(N_t^{(k)},L_t^{(k)})$, $t\geq0$, is a…

Probability · Mathematics 2009-09-29 Alexander Lindner , Ken-iti Sato

We present experimental and numerical results for the long-range fluctuation properties in the spectra of quantum graphs with chaotic classical dynamics and preserved time-reversal invariance. Such systems are generally believed to provide…

Chaotic Dynamics · Physics 2017-05-10 Barbara Dietz , Vitalii Yunko , Malgorzata Bialous , Szymon Bauch , Michal Lawniczak , Leszek Sirko

Model reparametrization, which follows the change-of-variable rule of calculus, is a popular way to improve the training of neural nets. But it can also be problematic since it can induce inconsistencies in, e.g., Hessian-based flatness…

Machine Learning · Computer Science 2023-10-24 Agustinus Kristiadi , Felix Dangel , Philipp Hennig

Permutation approach is suggested as a method to investigate financial time series in micro scales. The method is used to see how high frequency trading in recent years has affected the micro patterns which may be seen in financial time…

Statistical Finance · Quantitative Finance 2014-08-06 Cina Aghamohammadi , Mehran Ebrahimian , Hamed Tahmooresi

Periodic point sets model all solid crystalline materials whose structures are determined in a rigid form and should be studied up to rigid motion or isometry preserving inter-point distances. In 2021 H.Edelsbrunner et al. introduced an…

Computational Geometry · Computer Science 2022-05-05 Olga Anosova , Vitaliy Kurlin

Unitary Evolution Recurrent Neural Networks (uRNNs) have three attractive properties: (a) the unitary property, (b) the complex-valued nature, and (c) their efficient linear operators. The literature so far does not address -- how critical…

Machine Learning · Computer Science 2019-06-07 Izhak Shafran , Tom Bagby , R. J. Skerry-Ryan

The notion of $c$-differential uniformity has recently received a lot of attention since its proposal~\cite{Ellingsen}, and recently a characterization of perfect $c$-nonlinear functions in terms of difference sets in some quasigroups was…

Information Theory · Computer Science 2023-07-21 Kirpa Garg , Sartaj Ul Hasan , Pantelimon Stanica

Turing patterns are stationary, wave-like structures that emerge from the nonequilibrium assembly of reactive and diffusive components. While they are foundational in biophysics, their classical formulation relies on a single characteristic…

Soft Condensed Matter · Physics 2026-01-30 Siamak Mirfendereski , Ankur Gupta

Products and sums of random matrices have seen a rapid development in the past decade due to various analytical techniques available. Two of these are the harmonic analysis approach and the concept of polynomial ensembles. Very recently, it…

Probability · Mathematics 2023-02-02 Mario Kieburg

In this paper, we give out a setting of an Diaconis and Freedman's chain in a multidimensional simplex and consider its asymptotic behavior. By using techniques in random iterated functions theory and quasi-compact operators theory, we…

Probability · Mathematics 2020-06-04 Marc Peigné , Tat Dat Tran

Dirichlet's $L$-functions are natural extensions of the Riemann zeta function. In this paper we first give a brief survey of Ap\'ery-like series for some special values of the zeta function and certain $L$-functions. Then, we establish two…

Number Theory · Mathematics 2016-01-13 Zhi-Wei Sun

Linear fractional Galton-Watson branching processes in i.i.d.~random environment are, on the quenched level, intimately connected to random difference equations by the evolution of the random parameters of their linear fractional marginals.…

Probability · Mathematics 2021-10-01 Gerold Alsmeyer

Linear second order recursive sequences with arbitrary initial conditions are studied. For sequences with the same parameters a ring and a group is attached, and isomorphisms and homomorphisms are established for related parameters. In the…

Number Theory · Mathematics 2025-01-31 Zbigniew Lipinski , Maciej P. Wojtkowski

We use the theory of symmetric functions to enumerate various classes of alternating permutations w of {1,2,...,n}. These classes include the following: (1) both w and w^{-1} are alternating, (2) w has certain special shapes, such as…

Combinatorics · Mathematics 2007-05-23 Richard P. Stanley

Three similar convergence notions are considered. Two of them are the long established notions of convergent dynamics and incremental stability. The other is the more recent notion of contraction analysis. All three convergence notions…

Optimization and Control · Mathematics 2018-11-06 Duc N. Tran , Björn S. Rüffer , Christopher M. Kellett

Neural networks are powerful predictive models, but they provide little insight into the nature of relationships between predictors and outcomes. Although numerous methods have been proposed to quantify the relative contributions of input…

Methodology · Statistics 2023-01-30 Francesca Mandel , Ian Barnett
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