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Although asymptotic analyses of undirected network models based on degree sequences have started to appear in recent literature, it remains an open problem to study statistical properties of directed network models. In this paper, we…

Statistics Theory · Mathematics 2016-01-13 Ting Yan , Chenlei Leng , Ji Zhu

Random walks as well as diffusions in random media are considered. Methods are developed that allow one to establish large deviation results for both the `quenched' and the `averaged' case.

Probability · Mathematics 2007-05-23 S R S Varadhan

A powerful existing technique for evaluating statistical mechanical quantities in two-dimensional Ising models is based on constructing a matrix representing the nearest neighbor spin couplings and then evaluating the Pfaffian of the…

Disordered Systems and Neural Networks · Physics 2013-04-16 Creighton K. Thomas , A. Alan Middleton

The focus of this work is on estimation of the in-degree distribution in directed networks from sampling network nodes or edges. A number of sampling schemes are considered, including random sampling with and without replacement, and…

Methodology · Statistics 2018-10-03 Nelson Antunes , Shankar Bhamidi , Tianjian Guo , Vladas Pipiras , Bang Wang

This paper explores an eclectic range of path-planning methodologies engineered for rolling surfaces. Our focus is on the kinematic intricacies of rolling contact systems, which are investigated through a motion planning lens. Beyond…

Robotics · Computer Science 2025-01-09 Seyed Amir Tafrishi , Mikhail Svinin , Kenji Tahara

Based only on the information gathered in a snapshot of a directed network, we present a formal way of checking if the proposed model is correct for the empirical growing network under study. In particular, we show how to estimate the…

Physics and Society · Physics 2007-05-23 Daniel Fraiman

In my thesis I study mesoscopic corrections on diffuse transport. I first describe the diffuse transport of light, using the scalar approximation and the radiative transfer approach. Next, I focus on the correlations in transmission, I…

Condensed Matter · Physics 2007-05-23 M. C. W. van Rossum

Information theoretical measures, such as entropy, mutual information, and various divergences, exhibit robust characteristics in image registration applications. However, the estimation of these quantities is computationally intensive in…

Information Theory · Computer Science 2012-10-03 Zoltan Szabo , Andras Lorincz

We study the dynamics of macroscopic observables such as the magnetization and the energy per degree of freedom in Ising spin models on random graphs of finite connectivity, with random bonds and/or heterogeneous degree distributions. To do…

Disordered Systems and Neural Networks · Physics 2009-11-11 J. P. L. Hatchett , I. Pérez Castillo , A. C. C. Coolen , N. S. Skantzos

In this report, the explicit probability density functions of the random Euclidean distances associated with regular hexagons are given, when the two endpoints of a link are randomly distributed in the same hexagon, and two adjacent…

General Mathematics · Mathematics 2021-01-26 Yanyan Zhuang , Jianping Pan

Exact calculations of transmission and reflection coefficients in surface randomly corrugated optical waveguides are presented. As the length of the corrugated part of the waveguide increases, there is a strong preference to forward…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Garcia-Martin , J. A. Torres , J. J. Saenz , M. Nieto-Vesperinas

As a newly emerging advance in deep generative models, diffusion models have achieved state-of-the-art results in many fields, including computer vision, natural language processing, and molecule design. The remote sensing (RS) community…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Yidan Liu , Jun Yue , Shaobo Xia , Pedram Ghamisi , Weiying Xie , Leyuan Fang

Diffusion models (DMs) have been investigated in various domains due to their ability to generate high-quality data, thereby attracting significant attention. However, similar to traditional deep learning systems, there also exist potential…

Cryptography and Security · Computer Science 2025-09-30 Kang Wei , Xin Yuan , Fushuo Huo , Chuan Ma , Long Yuan , Songze Li , Ming Ding , Dacheng Tao

High-dimensional data sets are commonly collected in many contemporary applications arising in various fields of scientific research. We present two views of finite samples in high dimensions: a probabilistic one and a nonprobabilistic one.…

Statistics Theory · Mathematics 2013-11-13 Jinchi Lv

A generalization of Gauss's principle is used to derive the error laws corresponding to Types II and VII distributions in Pearson's classification scheme. Student's $r$-pdf (Type II) governs the distribution of the internal energy of a…

Statistical Mechanics · Physics 2011-10-25 B. H. Lavenda

We consider a directed percolation process on an ${\cal M}$ x ${\cal N}$ rectangular lattice whose vertical edges are directed upward with an occupation probability y and horizontal edges directed toward the right with occupation…

Statistical Mechanics · Physics 2007-05-23 L. C. Chen , F. Y. Wu

We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

We train a set of Restricted Boltzmann Machines (RBMs) on one- and two-dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations. We validate the training procedure by monitoring several…

Computational Physics · Physics 2019-08-14 Guido Cossu , Luigi Del Debbio , Tommaso Giani , Ava Khamseh , Michael Wilson

Following numerous earlier studies, extensive simulations and analyses were made on the continuous interaction distribution Gaussian model and the discrete bimodal interaction distribution Ising Spin Glass (ISG) models in dimension two…

Disordered Systems and Neural Networks · Physics 2017-04-12 P. H. Lundow , I. A. Campbell

The problem at the heart of this tutorial consists in modeling the path choice behavior of network users. This problem has been extensively studied in transportation science, where it is known as the route choice problem. In this…

Machine Learning · Statistics 2022-06-10 Maëlle Zimmermann , Emma Frejinger