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Continuous graph neural models based on differential equations have expanded the architecture of graph neural networks (GNNs). Due to the connection between graph diffusion and message passing, diffusion-based models have been widely…

Machine Learning · Computer Science 2024-04-01 Kaiyuan Cui , Xinyan Wang , Zicheng Zhang , Weichen Zhao

We prove an averaging principle which asserts convergence of diffusion processes on domains separated by semi-permeable membranes, when diffusion coefficients tend to infinity while the flux through the membranes remains constant. In the…

Functional Analysis · Mathematics 2019-08-08 Adam Bobrowski , Bogdan Kazmierczak , Markus Kunze

We derive the steady state properties of a general directed ``sandpile'' model in one dimension. Using a central limit theorem for dependent random variables we find the precise conditions for the model to belong to the universality class…

Statistical Mechanics · Physics 2009-11-11 M A Stapleton , K Christensen

Axelrod's model for the dissemination of culture contains two key factors required to model the process of diffusion of innovations, namely, social influence (i.e., individuals become more similar when they interact) and homophily (i.e.,…

Physics and Society · Physics 2015-12-09 Paulo F. C. Tilles , José F. Fontanari

Single-file diffusion refers to the motion in narrow channels of particles which cannot bypass each other. These strong correlations between particles lead to tracer subdiffusion, which has been observed in contexts as varied as transport…

Statistical Mechanics · Physics 2021-12-08 Alexis Poncet , Aurélien Grabsch , Pierre Illien , Olivier Bénichou

The present paper is concerned with diffusion processes running on tubular domains with conditions on nonreaching the boundary, respectively, reflecting at the boundary, and corresponding processes in the limit where the thin tubular…

Probability · Mathematics 2012-10-15 Sergio Albeverio , Seiichiro Kusuoka

Diffusion models have established themselves as state-of-the-art generative models across various data modalities, including images and videos, due to their ability to accurately approximate complex data distributions. Unlike traditional…

Machine Learning · Computer Science 2025-10-23 Daniel Wesego

We consider the edge-triangle model, a two-parameter family of exponential random graphs in which dependence between edges is introduced through triangles. In the so-called replica symmetric regime, the limiting free energy exists together…

Probability · Mathematics 2023-01-31 Alessandra Bianchi , Francesca Collet , Elena Magnanini

Diffusion models are a class of generative models that serve to establish a stochastic transport map between an empirically observed, yet unknown, target distribution and a known prior. Despite their remarkable success in real-world…

Machine Learning · Computer Science 2025-03-13 Puheng Li , Zhong Li , Huishuai Zhang , Jiang Bian

We study combinatorial aspects of the sandpile model on wheel and fan graphs, seeking bijective characterisations of the model's recurrent configurations on these families. For wheel graphs, we exhibit a bijection between these recurrent…

Combinatorics · Mathematics 2023-03-30 Thomas Selig

Avalanche dynamics is an indispensable feature of complex systems. Here we study the self-organized critical dynamics of avalanches on scale-free networks with degree exponent $\gamma$ through the Bak-Tang-Wiesenfeld (BTW) sandpile model.…

Statistical Mechanics · Physics 2007-05-23 D. -S. Lee , K. -I. Goh , B. Kahng , D. Kim

Superbubbles are acyclic induced subgraphs of a digraph with single entrance and exit that naturally arise in the context of genome assembly and the analysis of genome alignments in computational biology. These structures can be computed in…

This paper proposes and analyzes a novel clustering algorithm that combines graph-based diffusion geometry with techniques based on density and mode estimation. The proposed method is suitable for data generated from mixtures of…

Machine Learning · Statistics 2019-01-01 Mauro Maggioni , James M. Murphy

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We…

Soft Condensed Matter · Physics 2009-11-10 Brian Utter , R. P. Behringer

Prompted by recent experimental developments, a theory of surface scattering of fast atoms at grazing incidence is developed. The theory gives rise to a quantum mechanical limit for ordered surfaces that describes coherent diffraction peaks…

Atomic Physics · Physics 2022-09-23 J. R. Manson , Hocine Khemliche , Philippe Roncin

A recent work of Abbasi et al. [FOCS 2023] introduced the notion of $\varepsilon$-scatter dimension of a metric space and showed a general framework for efficient parameterized approximation schemes (so-called EPASes) for a wide range of…

Discrete Mathematics · Computer Science 2024-10-15 Romain Bourneuf , Marcin Pilipczuk

Light diffusion is usually associated with thick, opaque media. Indeed, multiple scattering is necessary for the onset of the diffusive regime and such condition is generally not met in almost transparent media. Nonetheless, at long enough…

We introduce the Density Formula for (topological) drawings of graphs in the plane or on the sphere, which relates the number of edges, vertices, crossings, and sizes of cells in the drawing. We demonstrate its capability by providing…

The sandpile group of a connected graph is the group of recurrent configurations in the abelian sandpile model on this graph. We study the structure of this group for the case of regular trees. A description of this group is the following:…

Combinatorics · Mathematics 2007-05-23 Evelin Toumpakari

We consider the classical evolution of a particle on a graph by using a time-continuous Frobenius-Perron operator which generalizes previous propositions. In this way, the relaxation rates as well as the chaotic properties can be defined…

Chaotic Dynamics · Physics 2009-10-31 F. Barra , P. Gaspard
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