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Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be probed analytically.…

Machine Learning · Computer Science 2023-12-18 Eddie Seabrook , Laurenz Wiskott

This paper investigates the application of KAM theory to the stochastic nonlinear Schr\"{o}dinger equation on infinite lattices, focusing on the stability of low-dimensional invariant tori in the sense of most probable paths. For…

Dynamical Systems · Mathematics 2025-08-26 Xinze Zhang , Yong Li , Kaizhi Wang

Ray flow methods provide efficient tools for modelling wave energy transport in complex systems at high-frequencies. We compare two Petrov-Galerkin discretizations of a phase-space boundary integral model for stationary wave energy…

Computational Physics · Physics 2023-10-02 David J. Chappell , Martin Richter , Gregor Tanner

We present a general non-parametric statistical inference theory for integrals of quantiles without assuming any specific sampling design or dependence structure. Technical considerations are accompanied by examples and discussions,…

Statistics Theory · Mathematics 2026-01-19 Nadezhda Gribkova , Mengqi Wang , Ričardas Zitikis

We study the equivalence classes under $\Delta^1_1$ isomorphism, otherwise effective-Borel isomorphism, between complete separable metric spaces which admit a recursive presentation and we show the existence of strictly increasing and…

Logic · Mathematics 2017-01-16 Vassilios Gregoriades

Inferring topological characteristics of complex networks from observed data is critical to understand the dynamical behavior of networked systems, ranging from the Internet and the World Wide Web to biological networks and social networks.…

Multiagent Systems · Computer Science 2020-05-13 Chunheng Jiang , Jianxi Gao , Malik Magdon-Ismail

We study spanning trees on Sierpinski graphs (i.e., finite approximations to the Sierpinski gasket) that are chosen uniformly at random. We construct a joint probability space for uniform spanning trees on every finite Sierpinski graph and…

Probability · Mathematics 2015-01-14 Masato Shinoda , Elmar Teufl , Stephan Wagner

Binomial Cayley graphs are obtained by considering the binomial coefficient of the weight function of a given Cayley graph and a natural number. We introduce these objects and study two families: one associated with symmetric groups and the…

Combinatorics · Mathematics 2024-09-06 Bernat Bassols-Cornudella , Francesco Viganò

In the paper we completely describe characters (central positive-definite functions) of simple locally finite groups that can be represented as inductive limits of (products of) symmetric groups under block diagonal embeddings. Each such…

Representation Theory · Mathematics 2011-06-01 Artem Dudko , Konstantin Medynets

The increasing availability of network data has driven the development of advanced statistical models specifically designed for metric graphs, where Gaussian processes play a pivotal role. While models such as Whittle-Mat\'ern fields have…

Methodology · Statistics 2026-03-18 David Bolin , Lenin Riera-Segura , Alexandre B. Simas

This paper introduces graphemes for constructing and analyzing stochastic processes that describe the evolution of large dynamic graphs. Unlike graphons, which capture the static properties of dense graphs via exchangeability or subgraph…

Probability · Mathematics 2025-04-16 Andreas Greven , Frank den Hollander , Anton Klimovsky , Anita Winter

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a {\em stochastic maximal inequality} derived by using the formula for…

Probability · Mathematics 2017-08-16 Yoichi Nishiyama

The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define…

Computational Geometry · Computer Science 2020-10-01 Frank Nielsen , Jean-Daniel Boissonnat , Richard Nock

Many enumeration problems in combinatorics, including such fundamental questions as the number of regular graphs, can be expressed as high-dimensional complex integrals. Motivated by the need for a systematic study of the asymptotic…

Combinatorics · Mathematics 2017-12-29 Mikhail Isaev , Brendan D. McKay

In the context of noncommutative geometry, we consider quiver representations -- not on vector spaces, as traditional, but on finite-dimensional prespectral triples (`discrete topological noncommutative spaces'). A similar idea appeared in…

Representation Theory · Mathematics 2025-02-20 Carlos I. Perez-Sanchez

We study a class of simple dimension groups in which the cyclic subgroup generated by the order unit is replaced by a copy of $\mathbb{Z}^{2}$ satisfying some strict conditions. Our main results are necessary and sufficient conditions on a…

Dynamical Systems · Mathematics 2025-10-01 Thierry Giordano , Ian F. Putnam , Christian F. Skau

This paper deals with the estimation of the unknown distribution of hidden random variables from the observation of pairwise comparisons between these variables. This problem is inspired by recent developments on Bradley-Terry models in…

Statistics Theory · Mathematics 2018-08-27 Sylvain Le Corff , Matthieu Lerasle , Elodie Vernet

For each integer $m \geq 1$, we construct a finite-dimensional family of rational maps, given by Blaschke-type products, whose restriction to the unit circle consists of $2m$-multimodal maps. We show that every post-critically finite…

Dynamical Systems · Mathematics 2026-05-08 Edson de Faria , Welington de Melo , Pedro A. S. Salomão , Edson Vargas

We discuss asymptotics of large Boltzmann random planar maps such that every vertex of degree $k$ has weight of order $k^{-2}$. Infinite maps of that kind were studied by Budd, Curien and Marzouk. These maps can be seen as the dual of the…

Probability · Mathematics 2024-03-11 Emmanuel Kammerer

The Entropy method provides a powerful framework for proving scalar concentration inequalities by establishing functional inequalities like Poincare and log-Sobolev inequalities. These inequalities are especially useful for deriving…

Probability · Mathematics 2020-11-30 Tarun Kathuria
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