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Over the past few years, research on deep graph learning has shifted from static graphs to temporal graphs in response to real-world complex systems that exhibit dynamic behaviors. In practice, temporal graphs are formalized as an ordered…

Machine Learning · Computer Science 2024-10-30 Jintang Li , Ruofan Wu , Xinzhou Jin , Boqun Ma , Liang Chen , Zibin Zheng

We study the abelian sandpile model on a random binary tree. Using a transfer matrix approach introduced by Dhar & Majumdar, we prove exponential decay of correlations, and in a small supercritical region (i.e., where the branching process…

Probability · Mathematics 2015-06-04 Frank Redig , Ellen Saada , Wioletta Ruszel

A two state sandpile model with preferential sand distribution is developed and studied numerically on scale free networks with power-law degree ($k$) distribution, {\em i.e.}: $P_k\sim k^{-\alpha}$. In this model, upon toppling of a…

Statistical Mechanics · Physics 2017-05-31 Himangsu Bhaumik , S. B. Santra

In this paper, we study the stationary distributions for the stochastic vertex models. Our main focus is the stochastic six vertex (S6V) model. We show that the extremal stationary distributions of the S6V model are given by product…

Probability · Mathematics 2023-03-23 Yier Lin

Finding communities in networks is a problem that remains difficult, in spite of the amount of attention it has recently received. The Stochastic Block-Model (SBM) is a generative model for graphs with "communities" for which, because of…

Machine Learning · Statistics 2021-04-22 Yali Wan , Marina Meila

Many inference problems, notably the stochastic block model (SBM) that generates a random graph with a hidden community structure, undergo phase transitions as a function of the signal-to-noise ratio, and can exhibit hard phases in which…

Disordered Systems and Neural Networks · Physics 2019-04-09 Federico Ricci-Tersenghi , Guilhem Semerjian , Lenka Zdeborova

The stochastic block model (SBM) is a random graph model with different group of vertices connecting differently. It is widely employed as a canonical model to study clustering and community detection, and provides a fertile ground to study…

Probability · Mathematics 2023-10-26 Emmanuel Abbe

We study a general mass transport model on an arbitrary graph consisting of $L$ nodes each carrying a continuous mass. The graph also has a set of directed links between pairs of nodes through which a stochastic portion of mass, chosen from…

Statistical Mechanics · Physics 2007-05-23 M. R. Evans , Satya N. Majumdar , R. K. P. Zia

We introduce a new random graph model motivated by biological questions relating to speciation. This random graph is defined as the stationary distribution of a Markov chain on the space of graphs on $\{1, \ldots, n\}$. The dynamics of this…

Probability · Mathematics 2019-06-24 François Bienvenu , Florence Débarre , Amaury Lambert

I define the Standard Supersymmetric Model (SSM) as the minimal supersymmetric extension ofthe Standard Model with gauge coupling unification and universal soft supersymmetry breaking at the unification scale. This well-defined model has a…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Kelley

We introduce computational methods that allow for effective estimation of a flexible, parametric non-stationary spatial model when the field size is too large to compute the multivariate normal likelihood directly. In this method, the field…

Computation · Statistics 2018-09-20 Amanda Muyskens , Joseph Guinness , Montserrat Fuentes

We present and analyze a model of an evolving sandpile surface in (2 + 1) dimensions where the dynamics of mobile grains ({\rho}(x, t)) and immobile clusters (h(x, t)) are coupled. Our coupling models the situation where the sandpile is…

Statistical Mechanics · Physics 2012-06-26 Bandan Chakrabortty , Anita Mehta

We study the abelian sandpile model in two dimensions on a directed cylindrical lattice with periodic transverse boundary conditions in the transverse direction and dissipation at one boundary. Recurrent configurations form a finite abelian…

Statistical Mechanics · Physics 2026-05-18 Abdul Quadir , Nikita Kalinin , Ram Ramaswamy

We perform large scale numerical simulations of a directed version of the two-state stochastic sandpile model. Numerical results show that this stochastic model defines a new universality class with respect to the Abelian directed sandpile.…

Statistical Mechanics · Physics 2009-10-31 Romualdo Pastor-Satorras , Alessandro Vespignani

Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon. In…

Machine Learning · Computer Science 2014-04-17 Navodit Misra , Ercan E. Kuruoglu

We analyze an optimal stopping problem for random walk in random scenery on general graphs, and determine when it has a finite optimum. We use this to extend a theorem of Levine, Murugan, Peres, and Ugurcan [2016]. They proved that on a…

Probability · Mathematics 2026-04-16 Ahmed Bou-Rabee , Yuval Peres , Ecaterina Sava-Huss

Networks, which represent agents and interactions between them, arise in myriad applications throughout the sciences, engineering, and even the humanities. To understand large-scale structure in a network, a common task is to cluster a…

Social and Information Networks · Computer Science 2019-05-22 Zachary M. Boyd , Mason A. Porter , Andrea L. Bertozzi

We check the universality properties of the two-dimensional Abelian sandpile model by computing some of its properties on the honeycomb lattice. Exact expressions for unit height correlation functions in presence of boundaries and for…

Statistical Mechanics · Physics 2011-02-16 N. Azimi-Tafreshi , H. Dashti-Naserabadi , S. Moghimi-Araghi , P. Ruelle

We insert some asymmetries in the continuous Abelian sandpile models, such as directedness and ellipticity. We analyze probability distribution of different heights and also find the field theory corresponding to the models. Also we find…

Statistical Mechanics · Physics 2009-11-13 N. Azimi-Tafreshi , H. Dashti-Naserabadi , S. Moghimi-Araghi

Stochastic Structural Stability Theory (SSST) provides an autonomous, deterministic, nonlinear dynamical system for evolving the statistical mean state of a turbulent system. In this work SSST is applied to the problem of understanding the…

Fluid Dynamics · Physics 2014-12-30 Brian F. Farrell , Petros J. Ioannou
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