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We present an alternative finite-size approach to a set of parity conserving interfaces involving attachment, dissociation, and detachment of extended objects in 1+1 dimensions. With the aid of a nonlocal construct introduced by Barma and…

Statistical Mechanics · Physics 2013-12-02 M. Arlego , M. D. Grynberg

Probabilistic dependency graphs (PDGs) are a flexible class of probabilistic graphical models, subsuming Bayesian Networks and Factor Graphs. They can also capture inconsistent beliefs, and provide a way of measuring the degree of this…

Data Structures and Algorithms · Computer Science 2023-11-10 Oliver E. Richardson , Joseph Y. Halpern , Christopher De Sa

We consider a random interval splitting process, in which the splitting rule depends on the empirical distribution of interval lengths. We show that this empirical distribution converges to a limit almost surely as the number of intervals…

Probability · Mathematics 2018-06-20 Pascal Maillard , Elliot Paquette

We present a simple one dimensional stochastic model with three control parameters and a surprisingly rich zoo of phase transitions. At each (discrete) site $x$ and time $t$, an integer $n(x,t)$ satisfies a linear interface equation with…

Statistical Mechanics · Physics 2023-04-21 Peter Grassberger , Deepak Dhar , P. K. Mohanty

To estimate a sparse linear model from data with Gaussian noise, consilience from lasso and compressed sensing literatures is that thresholding estimators like lasso and the Dantzig selector have the ability in some situations to identify…

Machine Learning · Statistics 2017-08-14 Jairo Diaz-Rodriguez , Sylvain Sardy

We consider gradient models on the lattice $Z^d$. These models serve as effective models for interfaces and are also known as continuous Ising models. The height of the interface is modelled by a random field with an energy which is a…

Mathematical Physics · Physics 2020-07-22 Susanne Hilger

In this paper, we study the risk bounds for samples independently drawn from an infinitely divisible (ID) distribution. In particular, based on a martingale method, we develop two deviation inequalities for a sequence of random variables of…

Machine Learning · Statistics 2012-02-20 Chao Zhang , Dacheng Tao

Growth processes and interface fluctuations can be studied through the properties of global quantities. We here discuss a global quantity that not only captures better the roughness of an interface than the widely studied surface width, but…

Statistical Mechanics · Physics 2015-06-03 Yen-Liang Chou , Michel Pleimling

Global physical properties of random media change qualitatively at a percolation threshold, where isolated clusters merge to form one infinite connected component. The precise knowledge of percolation thresholds is thus of paramount…

Statistical Mechanics · Physics 2008-01-13 Richard A. Neher , Klaus Mecke , Herbert Wagner

We propose a novel Bayesian methodology which uses random walks for rapid inference of statistical properties of undirected networks with weighted or unweighted edges. Our formalism yields high-accuracy estimates of the probability…

Physics and Society · Physics 2018-07-25 Willow B. Kion-Crosby , Alexandre V. Morozov

The dynamics of critical slope self-organized critical models is studied, using a previous mapping into a linear interface depinning model dragged at one end. The model is solved obtaining the complete set of scaling exponents. Some results…

Condensed Matter · Physics 2007-05-23 Alexei Vazquez , Oscar Sotolongo-Costa

We investigate solid-on-solid models that belong to the Kardar-Parisi-Zhang (KPZ) universality class on substrates that expand laterally at a constant rate by duplication of columns. Despite the null global curvature, we show that all…

Statistical Mechanics · Physics 2014-12-23 I. S. S. Carrasco , K. A. Takeuchi , S. C. Ferreira , T. J. Oliveira

We suggest an explanation of typical incubation times statistical features based on the universal behavior of exit times for diffusion models. We give a mathematically rigorous proof of the characteristic right skewness of the incubation…

Quantitative Methods · Quantitative Biology 2018-04-18 Yuri Bakhtin

We use deposition models of kinetic roughening of a growing surface to introduce the concepts of universality and scaling and to analyze the qualitative and quantitative role of different parameters. In particular, we focus on two classes…

Statistical Mechanics · Physics 2018-08-06 Alessandro Santini , Paolo Politi

In this paper, we consider objective Bayesian inference of the generalized exponential distribution using the independence Jeffreys prior and validate the propriety of the posterior distribution under a family of structured priors. We…

Methodology · Statistics 2023-09-26 Aojun Li , Keying Ye , Min Wang

Dependency networks (Heckerman et al., 2000) provide a flexible framework for modeling complex systems with many variables by combining independently learned local conditional distributions through pseudo-Gibbs sampling. Despite their…

Machine Learning · Computer Science 2026-04-02 Kazuya Takabatake , Shotaro Akaho

The analytical characterization of coverage probability in finite three-dimensional wireless networks has long remained an open problem, hindered by the loss of spatial independence in finite-node settings and the coupling between link…

Networking and Internet Architecture · Computer Science 2025-11-03 Yunfeng Jiang , Zhiming Huang , Jianping Pan

We consider the scaling limit of a generic ferromagnetic system with a continuous phase transition, on the half plane with boundary conditions leading to the equilibrium of two different phases below criticality. We use general properties…

Statistical Mechanics · Physics 2014-10-09 Gesualdo Delfino , Alessio Squarcini

Interfaces in a model with a single, real nonconserved order parameter and purely dissipative evolution equation are considered. We show that a systematic perturbative approach, called the expansion in width and developed for curved domain…

Soft Condensed Matter · Physics 2009-10-31 H. Arodz , R. Pelka

We develop a framework for generalized variational inference in infinite-dimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI). GWI leverages the Wasserstein distance between Gaussian…

Machine Learning · Statistics 2022-10-18 Veit D. Wild , Robert Hu , Dino Sejdinovic
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