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We introduce a new information-geometric structure associated with the dynamics on discrete objects such as graphs and hypergraphs. The presented setup consists of two dually flat structures built on the vertex and edge spaces,…

Information Theory · Computer Science 2023-08-08 Tetsuya J. Kobayashi , Dimitri Loutchko , Atsushi Kamimura , Shuhei A. Horiguchi , Yuki Sughiyama

In information geometry, one of the basic problem is to study the geomet-ric properties of statistical manifold. In this paper, we study the geometricstructure of the generalized normal distribution manifold and show that it has constant…

Differential Geometry · Mathematics 2019-04-05 Mingao Yuan

We give a simple probabilistic description of a transition between two states which leads to a generalized escort distribution. When the parameter of the distribution varies, it defines a parametric curve that we call an escort-path. The…

Statistical Mechanics · Physics 2012-06-05 J. -F. Bercher

We present an extension of Voronoi diagrams where when considering which site a client is going to use, in addition to the site distances, other site attributes are also considered (for example, prices or weights). A cell in this diagram is…

Computational Geometry · Computer Science 2016-08-24 Hsien-Chih Chang , Sariel Har-Peled , Benjamin Raichel

We study Voronoi diagrams for distance functions that add together two convex functions, each taking as its argument the difference between Cartesian coordinates of two planar points. When the functions do not grow too quickly, then the…

Computational Geometry · Computer Science 2010-05-14 Matthew Dickerson , David Eppstein , Kevin A. Wortman

Probabilistic circuits (PCs) enable exact and tractable inference but employ data independent mixture weights that limit their ability to capture local geometry of the data manifold. We propose Voronoi tessellations (VT) as a natural way to…

Machine Learning · Computer Science 2026-03-13 Sahil Sidheekh , Sriraam Natarajan

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our…

Statistical Mechanics · Physics 2011-11-30 Diego Luis Gonzalez Cabrera , T. L. Einstein

Technology of data collection and information transmission is based on various mathematical models of encoding. The words "Geometry of information" refer to such models, whereas the words "Moufang patterns" refer to various sophisticated…

Information Theory · Computer Science 2022-03-03 Noemie Combe , Yuri I. Manin , Matilde Marcolli

Voronoi diagrams appear in many areas in science and technology and have numerous applications. They have been the subject of extensive investigation during the last decades. Roughly speaking, they are a certain decomposition of a given…

Computational Geometry · Computer Science 2015-03-19 Daniel Reem

We study Voronoi diagrams of manifolds and varieties with respect to polyhedral norms. We provide upper and lower bounds on the dimensions of Voronoi cells. For algebraic varieties, we count their full-dimensional Voronoi cells. As an…

Algebraic Geometry · Mathematics 2022-09-26 Adrian Becedas , Kathlén Kohn , Lorenzo Venturello

This introductory text arises from a lecture given in G\"oteborg, Sweden, given by the first author and is intended for undergraduate students, as well as for any mathematically inclined reader wishing to explore a synthesis of ideas…

Differential Geometry · Mathematics 2025-02-18 Noémie C. Combe , Philippe G. Combe , Hanna K. Nencka

We study random graphs with latent geometric structure, where the probability of each edge depends on the underlying random positions corresponding to the two endpoints. We focus on the setting where this conditional probability is a…

Probability · Mathematics 2021-11-01 Suqi Liu , Miklos Z. Racz

A family of replicator-like dynamics, called the escort replicator equation, is constructed using information-geometric concepts and generalized information entropies and diverenges from statistical thermodynamics. Lyapunov functions and…

Dynamical Systems · Mathematics 2012-02-27 Marc Harper

This is the second of two papers that introduce a deformation theoretic framework to explain and broaden a link between homotopy algebra and probability theory. This paper outlines how the framework can assist in the development of homotopy…

Probability · Mathematics 2014-04-02 Gabriel C. Drummond-Cole , Jae-Suk Park , John Terilla

We define a class of probability distributions that we call simplicial mixture models, inspired by simplicial complexes from algebraic topology. The parameters of these distributions represent their topology and we show that it is possible…

Statistics Theory · Mathematics 2019-09-24 James T. Griffin

In this paper, we introduce the concept of principal bundles on statistical manifolds. After necessary preliminaries on information geometry and principal bundles on manifolds, we study the $\alpha$-structure of frame bundles over…

Differential Geometry · Mathematics 2014-04-29 Didong Li , Huafei Sun , Chen Tao , Lin Jiu

The round-trip distance function on a geographic network (such as a road network, flight network, or utility distribution grid) defines the "distance" from a single vertex to a pair of vertices as the minimum length tour visiting all three…

Data Structures and Algorithms · Computer Science 2019-09-04 Matthew T. Dickerson , Michael T. Goodrich , Thomas D. Dickerson

We introduce an information-theoretic framework for smooth structures on topological manifolds, replacing coordinate charts with small-scale entropy data of local probability probes. A concise set of axioms identifies admissible coordinate…

Differential Geometry · Mathematics 2026-01-21 Amandip Sangha

We show that the statistical manifold of normal distributions is homogeneous. In particular, it admits a $2$-dimensional solvable Lie group structure. In addition, we give a geometric characterization of the Amari-Chentsov…

Differential Geometry · Mathematics 2020-05-29 Hitoshi Furuhata , Jun-ichi Inoguchi , Shimpei Kobayashi

Statistical analysis of a graph often starts with embedding, the process of representing its nodes as points in space. How to choose the embedding dimension is a nuanced decision in practice, but in theory a notion of true dimension is…

Machine Learning · Statistics 2021-01-06 Patrick Rubin-Delanchy
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