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Generating graph-structured data is crucial in applications such as molecular generation, knowledge graphs, and network analysis. However, their discrete, unordered nature makes them difficult for traditional generative models, leading to…

Machine Learning · Computer Science 2026-04-14 Ole Petersen , Marcel Kollovieh , Marten Lienen , Stephan Günnemann

We study the steady state of the abelian sandpile models with stochastic toppling rules. The particle addition operators commute with each other, but in general these operators need not be diagonalizable. We use their abelian algebra to…

Statistical Mechanics · Physics 2010-10-01 Tridib Sadhu , Deepak Dhar

Diffusion models, as a novel generative paradigm, have achieved remarkable success in various image generation tasks such as image inpainting, image-to-text translation, and video generation. Graph generation is a crucial computational task…

Machine Learning · Computer Science 2023-08-29 Chengyi Liu , Wenqi Fan , Yunqing Liu , Jiatong Li , Hang Li , Hui Liu , Jiliang Tang , Qing Li

We extend the use of random evolving sets to time-varying conductance models and utilize it to provide tight heat kernel upper bounds. It yields the transience of any uniformly lazy random walk, on Z^d, d>=3, equipped with uniformly bounded…

Probability · Mathematics 2016-03-22 Amir Dembo , Ruojun Huang , Ben Morris , Yuval Peres

In the present paper a novel graph-based approach to the shape decomposition problem is addressed. The shape is appropriately transformed into a visibility graph enriched with local neighborhood information. A two-step diffusion process is…

Computer Vision and Pattern Recognition · Computer Science 2017-09-13 Foteini Fotopoulou , George Economou

Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challenge of having up to $n!$ such representations for graphs with $n$ nodes is only partially mitigated…

We introduce a natural Boltzmann measure over polyominoes induced by boundary avalanches in the Abelian Sandpile Model. Through the study of a suitable associated process, we give an argument suggesting that the probability distribution of…

Discrete Mathematics · Computer Science 2024-06-25 Andrea Sportiello

There are three fundamental physical processes that gives rise to the morphology of a surface: deposition, surface diffusion and desorption. The characteristics of the interfaces generated by the combination of deposition and surface…

Statistical Mechanics · Physics 2007-05-23 Juan R. Sanchez

We numerically study avalanches in the two dimensional Abelian sandpile model in terms of a sequence of waves of toppling events. Priezzhev et al [PRL 76, 2093 (1996)] have recently proposed exact results for the critical exponents in this…

Statistical Mechanics · Physics 2009-10-30 Maya Paczuski , Stefan Boettcher

We study the distribution of finite clusters in slightly supercritical ($p \downarrow p_c$) Bernoulli bond percolation on transitive nonamenable graphs, proving in particular that if $G$ is a transitive nonamenable graph satisfying the…

Probability · Mathematics 2022-07-28 Tom Hutchcroft

Starting from a unit mass on a vertex of a graph, we investigate the minimum number of "\emph{controlled diffusion}" steps needed to transport a constant mass $p$ outside of the ball of radius $n$. In a step of a controlled diffusion…

Combinatorics · Mathematics 2017-03-30 Laura Florescu , Yuval Peres , Miklos Z. Racz

Place an $A$-particle at each site of a graph independently with probability $p$ and otherwise place a $B$-particle. $A$- and $B$-particles perform independent continuous time random walks at rates $\lambda_A$ and $\lambda_B$, respectively,…

Probability · Mathematics 2023-08-02 Tobias Johnson , Matthew Junge , Hanbaek Lyu , David Sivakoff

Scale-free percolation is a percolation model on $\mathbb{Z}^d$ which can be used to model real-world networks. We prove bounds for the graph distance in the regime where vertices have infinite degrees. We fully characterize transience vs.…

Probability · Mathematics 2018-01-11 Markus Heydenreich , Tim Hulshof , Joost Jorritsma

Diffusion models have made significant contributions to computer vision, sparking a growing interest in the community recently regarding the application of them to graph generation. Existing discrete graph diffusion models exhibit…

Machine Learning · Computer Science 2024-05-07 Xingcheng Fu , Yisen Gao , Yuecen Wei , Qingyun Sun , Hao Peng , Jianxin Li , Xianxian Li

In the abelian sandpile model, recurrent chip configurations are of interest as they are a natural choice of coset representatives under the quotient of the reduced Laplacian. We investigate graphs whose recurrent identities with respect to…

Combinatorics · Mathematics 2020-09-07 Yibo Gao , Rupert Li

The paper develops one-parametric family of the sand-piles dealing with the grains' local losses on the fixed amount. The family exhibits the crossover between the models with deterministic and stochastic relaxation. The mean height of the…

Statistical Mechanics · Physics 2009-11-11 A. B. Shapoval , M. G. Shnirman

The modeling of diffusion processes on graphs is the basis for many network science and machine learning approaches. Entropic measures of network-based diffusion have recently been employed to investigate the reversibility of these…

Dynamical Systems · Mathematics 2025-10-23 Samuel Koovely , Alexandre Bovet

Motivated by the dissipative abelian sandpile model, we analyze the trajectories of a one-dimensional random walk in a landscape of soft traps. These traps, placed at increasing distances from each other, correspond to dissipative sites in…

Mathematical Physics · Physics 2025-07-09 Frank Redig , Ellen Saada , Berend van Tol

We introduce a one-dimensional sandpile model which incorporates particle inertia. The inertial dynamics are governed by a new parameter which, as it passes through a threshold value, alters the toppling dynamics in such a way that the…

Condensed Matter · Physics 2009-10-28 D. A. Head , G. J. Rodgers

We present a graph-based variational algorithm for multiclass classification of high-dimensional data, motivated by total variation techniques. The energy functional is based on a diffuse interface model with a periodic potential. We…

Machine Learning · Statistics 2012-12-06 Cristina Garcia-Cardona , Arjuna Flenner , Allon G. Percus