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Let $H=(V,E)$ be an $r$-uniform hypergraph with the vertex set $V$ and the edge set $E$. For $1\leq s \leq r/2$, we define a weighted graph $G^{(s)}$ on the vertex set ${V\choose s}$ as follows. Every pair of $s$-sets $I$ and $J$ is…

Combinatorics · Mathematics 2011-12-06 Linyuan Lu , Xing Peng

Every realistic instance of a percolation problem is faced with some degree of polydispersity, e.g., the pore-size distribution of an inhomogeneous medium, the size distribution of filler particles in composite materials, or the vertex…

Statistical Mechanics · Physics 2025-06-16 Fabian Coupette , Tanja Schilling

In the present study, we establish the existence of nontrivial site percolation threshold in the Relative Neighborhood Graph (RNG) for Poisson stationary point process with unit intensity in the plane.

Mathematical Physics · Physics 2010-05-02 Jean-Michel Billiot , Franck Corset , Eric Fontenas

In this work we develop a numerical method for solving a type of convex graph-structured tensor optimization problems. This type of problems, which can be seen as a generalization of multi-marginal optimal transport problems with…

Optimization and Control · Mathematics 2024-03-25 Axel Ringh , Isabel Haasler , Yongxin Chen , Johan Karlsson

Percolation theory has been largely used in the study of structural properties of complex networks such as the robustness, with remarkable results. Nevertheless, a purely topological description is not sufficient for a correct…

Statistical Mechanics · Physics 2016-08-31 Luca Dall'Asta

We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold. To efficiently reconstruct the level set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic…

Machine Learning · Statistics 2020-03-03 Xiong Lyu , Mickael Binois , Michael Ludkovski

We propose an efficient and robust iterative solution to the multi-object matching problem. We first clarify serious limitations of current methods as well as the inappropriateness of the standard iteratively reweighted least squares…

Computer Vision and Pattern Recognition · Computer Science 2021-10-11 Yunpeng Shi , Shaohan Li , Gilad Lerman

Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the…

Machine Learning · Computer Science 2017-07-19 Hermina Petric Maretic , Dorina Thanou , Pascal Frossard

This work develops a flexible and mathematically sound framework for the design and analysis of graph scattering networks with variable branching ratios and generic functional calculus filters. Spectrally-agnostic stability guarantees for…

Machine Learning · Computer Science 2023-01-30 Christian Koke , Gitta Kutyniok

As a fundamental structural transition in complex networks, core percolation is related to a wide range of important problems. Yet, previous theoretical studies of core percolation have been focusing on the classical Erd\H{o}s-R\'enyi…

Statistical Mechanics · Physics 2013-01-01 Yang-Yu Liu , Endre Csóka , Haijun Zhou , Márton Pósfai

We define an inhomogeneous percolation model on "ladder graphs" obtained as direct products of an arbitrary graph $G = (V,E)$ and the set of integers $\mathbb{Z}$ (vertices are thought of as having a "vertical" component indexed by an…

Probability · Mathematics 2019-03-19 Réka Szabó , Daniel Valesin

An exact solution to the problem of parametric level statistics in non-Gaussian ensembles of N by N Hermitian random matrices with either soft or strong level confinement is formulated within the framework of the orthogonal polynomial…

Statistical Mechanics · Physics 2009-10-31 E. Kanzieper

Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity of networks. However, there has been little research with…

Machine Learning · Statistics 2021-01-13 Yann Issartel

Data sets are growing in complexity thanks to the increasing facilities we have nowadays to both generate and store data. This poses many challenges to machine learning that are leading to the proposal of new methods and paradigms, in order…

Machine Learning · Computer Science 2018-12-04 Irene Córdoba , Concha Bielza , Pedro Larrañaga

Complex-valued signals are used in the modeling of many systems in engineering and science, hence being of fundamental interest. Often, random complex-valued signals are considered to be proper. A proper complex random variable or process…

Machine Learning · Computer Science 2015-02-19 Rafael Boloix-Tortosa , F. Javier Payán-Somet , Eva Arias-de-Reyna , Juan José Murillo-Fuentes

We consider a version of continuum long-range percolation on finite boxes of $\mathbb{R}^d$ in which the vertex set is given by the points of a Poisson point process and each pair of two vertices at distance $r$ is connected with…

Probability · Mathematics 2023-11-21 Ercan Sönmez

In this paper, we study the graph classification problem in vertex-labeled graphs. Our main goal is to classify the graphs comparing their higher-order structures thanks to heat diffusion on their simplices. We first represent…

Social and Information Networks · Computer Science 2020-07-02 Mehmet Emin Aktas , Esra Akbas

We study the problem of determining the distribution of vertices of a particular given type in the set of all Feynman tree graphs in quantum field theories. We show that in almost all cases a Gaussian distribution arises asymptotically, and…

High Energy Physics - Phenomenology · Physics 2011-09-13 Petros Draggiotis , Ronald Kleiss

We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of…

Numerical Analysis · Mathematics 2020-03-11 Andrew T. Barker , Stephan V. Gelever , Chak S. Lee , Sarah V. Osborn , Panayot S. Vassilevski

Because of the significant increase in size and complexity of the networks, the distributed computation of eigenvalues and eigenvectors of graph matrices has become very challenging and yet it remains as important as before. In this paper…

Numerical Analysis · Mathematics 2017-11-27 Konstantin Avrachenkov , Philippe Jacquet , Jithin Sreedharan