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This paper studies the $p$-biharmonic equation on graphs, which arises in point cloud processing and can be interpreted as a natural extension of the graph $p$-Laplacian from the perspective of hypergraph. The asymptotic behavior of the…

Analysis of PDEs · Mathematics 2025-04-28 Kehan Shi , Martin Burger

In this paper we study numerical approximations of the evolution problem for the nonlocal $p$-Laplacian operator with homogeneous Neumann boundary conditions on inhomogeneous random convergent graph sequences. More precisely, for networks…

Numerical Analysis · Mathematics 2018-05-07 Yosra Hafiene , Jalal Fadini , Christophe Chesneau , Abderrahim Elmoataz

As a generalization of graphs, hypergraphs are widely used to model higher-order relations in data. This paper explores the benefit of the hypergraph structure for the interpolation of point cloud data that contain no explicit structural…

Numerical Analysis · Mathematics 2025-03-18 Kehan Shi , Martin Burger

We consider point clouds obtained as random samples of a measure on a Euclidean domain. A graph representing the point cloud is obtained by assigning weights to edges based on the distance between the points they connect. Our goal is to…

Statistics Theory · Mathematics 2015-10-28 Nicolás García Trillos , Dejan Slepčev

We consider the Cauchy problem for the evolutive discrete p-Laplacian in infinite graphs, with initial data decaying at infinity. We prove optimal sup and gradient bounds for nonnegative solutions, when the initial data has finite mass, and…

Analysis of PDEs · Mathematics 2018-05-08 Daniele Andreucci , Anatoli F. Tedeev

Tackling semi-supervised learning problems with graph-based methods has become a trend in recent years since graphs can represent all kinds of data and provide a suitable framework for studying continuum limits, e.g., of differential…

Machine Learning · Computer Science 2022-02-07 Tim Roith , Leon Bungert

In this paper we study numerical approximations of the evolution problem for the nonlocal $p$-Laplacian with homogeneous Neumann boundary conditions. First, we derive a bound on the distance between two continuous-in-time trajectories…

Analysis of PDEs · Mathematics 2019-04-29 Hafiene Yosra , Jalal Fadili , Abderrahim Elmoataz

We investigate the limiting behavior of solutions to the inhomogeneous $p$-Laplacian equation $-\Delta_p u = \mu_p$ subject to Neumann boundary conditions. For right hand sides which are arbitrary signed measures we show that solutions…

Analysis of PDEs · Mathematics 2023-01-31 Leon Bungert

In this paper, we establish the well-posedness and large-time asymptotic behavior of viscosity solutions to singular/degenerate parabolic $p$-Laplacian equations with general capillary-type boundary conditions, including Neumann and…

Analysis of PDEs · Mathematics 2026-05-13 Zhenghuan Gao , Jin Yan , Yang Zhou

In this paper we consider a class of continuity equations that are conditioned to stay in general space-time domains, which is formulated as a continuum limit of interacting particle systems. Firstly, we study the well-posedness of the…

Analysis of PDEs · Mathematics 2018-06-12 Yuming Zhang

We observe that the Laplacian of a random graph G on N vertices represents and explicitly solvable model in the limit of infinitely increasing N. Namely, we derive recurrent relations for the limiting averaged moments of the adjacency…

Mathematical Physics · Physics 2007-05-23 A. Khorunzhy , V. Vengerovsky

We study a singularly perturbed problem related to infinity Laplacian operator with prescribed boundary values in a region. We prove that solutions are locally (uniformly) Lipschitz continuous, they grow as a linear function, are strongly…

Analysis of PDEs · Mathematics 2016-10-28 Gleydson Chaves Ricarte , João Vítor da Silva , Rafayel Teymurazyan

In this paper, we study a nonlocal variational problem which consists of minimizing in $L^2$ the sum of a quadratic data fidelity and a regularization term corresponding to the $L^p$-norm of the nonlocal gradient. In particular, we study…

Numerical Analysis · Mathematics 2019-08-21 Yosra Hafiene , Jalal Fadili , Abderrahim Elmoataz

In this article, we are interested in the Dirichlet problem for parabolic viscous Hamilton-Jacobi Equations. It is well-known that the gradient of the solution may blow up in finite time on the boundary of the domain, preventing a classical…

Analysis of PDEs · Mathematics 2013-11-15 Amal Attouchi , Guy Barles

We study a nonlinear porous medium type equation involving the infinity Laplacian operator. We first consider the problem posed on a bounded domain and prove existence of maximal nonnegative viscosity solutions. Uniqueness is obtained for…

Analysis of PDEs · Mathematics 2011-09-20 Manuel Portilheiro , Juan Luis Vazquez

Our purpose in this paper is to provide a self contained account of the inhomogeneous Dirichlet problem $\Delta_\infty u=f(x,u)$ where $u$ takes a prescribed continuous data on the boundary of bounded domains. We employ a combination of…

Analysis of PDEs · Mathematics 2011-06-29 Tilak Bhattacharya , Ahmed Mohammed

In this paper we study asymptotic behavior of solutions of obstacle problems for $p-$Laplacians as $p\to \infty.$ For the one-dimensional case and for the radial case, we give an explicit expression of the limit. In the n-dimensional case,…

Analysis of PDEs · Mathematics 2023-12-29 Raffaela Capitanelli , Maria Agostina Vivaldi

We study the asymptotic nature of geometric structures formed from a point cloud of observations of (generally heavy tailed) distributions in a Euclidean space of dimension greater than one. A typical example is given by the Betti numbers…

Probability · Mathematics 2016-01-11 Takashi Owada , Robert J. Adler

We provide an algorithm, running in polynomial time in the number of vertices, computing the unique solution to the biased infinity Laplacian Boundary Problem on finite graphs. The algorithm is based on the general outline and approach…

Combinatorics · Mathematics 2020-01-01 Yuval Peres , Zoran Sunic

We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it…

Machine Learning · Statistics 2026-02-24 Martin Andersson , Benny Avelin
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