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This article presents a multiscale, non-linear and directional statistical characterization of images based on the estimation of the skewness, flatness, entropy and distance from Gaussianity of the spatial increments. These increments are…

Fluid Dynamics · Physics 2023-10-11 Carlos Granero-Belinchon , Stéphane G. Roux , Nicolas B. Garnier

For the Jacobian resulting from the previously considered problem of the path integral reduction in Wiener path integrals for a mechanical system with symmetry describing the motion of two interacting scalar particles on a manifold that is…

Mathematical Physics · Physics 2020-07-10 S. N. Storchak

The Jacobi polynomials $\hat{P}_n^{(\alpha,\beta)}(x)$ conform the canonical family of hypergeometric orthogonal polynomials (HOPs) with the two-parameter weight function $(1-x)^\alpha (1+x)^\beta, \alpha,\beta>-1,$ on the interval…

Mathematical Physics · Physics 2021-10-25 Nahual Sobrino , Jesus S. Dehesa

Degree heterogeneity and latent geometry, also referred to as popularity and similarity, are key explanatory components underlying the structure of real-world networks. The relationship between these components and the statistical…

Social and Information Networks · Computer Science 2024-09-18 Keith Malcolm Smith , Jason P. Smith

We study information theoretic geometry in time dependent quantum mechanical systems. First, we discuss global properties of the parameter manifold for two level systems exemplified by i) Rabi oscillations and ii) quenching dynamics of the…

Statistical Mechanics · Physics 2016-05-05 Anshuman Dey , Suvankar Paul , Pratim Roy , Tapobrata Sarkar

We establish an exact information-geometric inequality that remains valid regardless of the underlying dynamics, encompassing both Markovian and non-Markovian evolutions within the mixed-state domain. This inequality can be viewed as an…

Quantum Physics · Physics 2026-04-24 T. Koide , A. van de Venn

There are many methods developed to approximate a cloud of vectors embedded in high-dimensional space by simpler objects: starting from principal points and linear manifolds to self-organizing maps, neural gas, elastic maps, various types…

Machine Learning · Statistics 2016-09-01 E. M. Mirkes , A. Zinovyev , A. N. Gorban

Information geometry provides a geometric approach to families of statistical models. The key geometric structures are the Fisher quadratic form and the Amari-Chentsov tensor. In statistics, the notion of sufficient statistic expresses the…

Statistics Theory · Mathematics 2015-05-27 Nihat Ay , Jürgen Jost , Hông Vân Lê , Lorenz Schwachhöfer

Partial differential equations describing compressible fluids are prone to the formation of shock singularities, arising from faster upstream fluid particles catching up to slower, downstream ones. In geometric terms, this causes the…

Analysis of PDEs · Mathematics 2026-01-07 Ruijia Cao , Florian Schäfer

The semidirect product of the real Heisenberg group ${\rm H}_1(\mathbb{R})$ with ${\rm SL}(2,\mathbb{R})$, called the real Jacobi group $G^J_1(\mathbb{R})$, admits a four-parameter invariant metric expressed in the S-coordinates. We…

Differential Geometry · Mathematics 2021-01-21 Stefan Berceanu

Latent manifolds of autoencoders provide low-dimensional representations of data, which can be studied from a geometric perspective. We propose to describe these latent manifolds as implicit submanifolds of some ambient latent space. Based…

Machine Learning · Computer Science 2026-01-30 Florine Hartwig , Josua Sassen , Juliane Braunsmann , Martin Rumpf , Benedikt Wirth

We study information-theoretic phase transitions for the detectability of latent geometry in bipartite random geometric graphs RGGs with Gaussian d-dimensional latent vectors while only a subset of edges carries latent information…

Probability · Mathematics 2026-04-13 Andreas Göbel , Marcus Pappik , Leon Schiller

Real algebraic geometry is the study of semi-algebraic sets, subsets of $\R^k$ defined by Boolean combinations of polynomial equalities and inequalities. The focus of this thesis is to study quantitative results in real algebraic geometry,…

Algebraic Geometry · Mathematics 2013-08-01 Salvador Barone

Geometrization of dynamics consists of representing trajectories by geodesics on a configuration space with a suitably defined metric. Previously, efforts were made to show that the analysis of dynamical stability can also be carried out…

Chaotic Dynamics · Physics 2015-07-14 Eduardo Cuervo-Reyes , Ramis Movassagh

We review a nonparametric version of Amari's Information Geometry in which the set of positive probability densities on a given sample space is endowed with an atlas of charts to form a differentiable manifold modeled on Orlicz Banach…

Statistics Theory · Mathematics 2015-06-17 Giovanni Pistone

We develop a language for describing the relationship among observations, mathematical models, and the underlying principles from which they are derived. Using Information Geometry, we consider geometric properties of statistical models for…

Data Analysis, Statistics and Probability · Physics 2016-07-14 Mark K. Transtrum , Gus Hart , Peng Qiu

This thesis is concerned with extending the idea of geodesic completeness from pseudo-Riemannian to complex geometry: we take, however a completely holomorphicpoint of view; that is to say, a 'metric' will be a (meromorphic) symmetric…

Complex Variables · Mathematics 2009-02-26 Claudio Meneghini

We present theory and practice for robust implementations of bivariate Jacobi set and Reeb space algorithms. Robustness is a fundamental topic in computational geometry that deals with the issues of numerical errors and degenerate cases in…

Computational Geometry · Computer Science 2025-10-10 Petar Hristov , Ingrid Hotz , Talha Bin Masood

Using the supersymmetric method of random matrix theory within the Heidelberg approach framework we provide statistical description of stationary intensity sampled in locations inside an open wave-chaotic cavity, assuming that the…

Disordered Systems and Neural Networks · Physics 2023-10-16 Yan V. Fyodorov , Elizaveta Safonova

We introduce a two parameter ($\alpha, \beta>-1$) family of interacting particle systems with determinantal correlation kernels expressible in terms of Jacobi polynomials $\{ P^{(\alpha, \beta)}_k \}_{k \geq 0}$. The family includes…

Probability · Mathematics 2017-08-08 Mark Cerenzia , Jeffrey Kuan
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