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Related papers: On the importance sampling of self-avoiding walks

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The study of random walks has increasingly been popular across diverse disciplines such as statistics, mathematics, quantum physics, where they are used to model paths consisting of successive random steps in a mathematical space. A…

Probability · Mathematics 2026-05-08 Puja Pandey , Palaniappan Vellaisamy

Accurately analyzing graph properties of social networks is a challenging task because of access limitations to the graph data. To address this challenge, several algorithms to obtain unbiased estimates of properties from few samples via a…

Social and Information Networks · Computer Science 2020-07-14 Kazuki Nakajima , Kazuyuki Shudo

This work focuses on the study of quantum stochastic walks, which are a generalization of coherent, i. e. unitary quantum walks. Our main goal is to present a measure of a coherence of the walk. To this end, we utilize the asymptotic…

Quantum Physics · Physics 2018-03-21 Krzysztof Domino , Adam Glos , Mateusz Ostaszewski , Łukasz Pawela , Przemysław Sadowski

Random walks are powerful tools to analyze spatial-temporal patterns produced by living organisms ranging from cells to humans. At the same time, it is evident that these patterns are not completely random but are results of a convolution…

Statistical Mechanics · Physics 2021-12-08 M. I. Krivonosov , S. N. Tikhomirov , S. Denisov

We present an affine-invariant random walk for drawing uniform random samples from a convex body $\mathcal{K} \subset \mathbb{R}^n$ that uses maximum volume inscribed ellipsoids, known as John's ellipsoids, for the proposal distribution.…

Machine Learning · Statistics 2020-07-24 Adam Gustafson , Hariharan Narayanan

It is well known that the isotonic least squares estimator is characterized as the derivative of the greatest convex minorant of a random walk. Provided the walk has exchangeable increments, we prove that the slopes of the greatest convex…

Statistics Theory · Mathematics 2018-12-12 Jake A. Soloff , Adityanand Guntuboyina , Jim Pitman

Improving Importance Sampling estimators for rare event probabilities requires sharp approx- imations of the optimal density leading to a nearly zero-variance estimator. This paper presents a new way to handle the estimation of the…

Statistics Theory · Mathematics 2014-01-15 Virgile Caron

In this paper analogies between different (dis)similarity matrices are derived. These matrices, which are connected to path enumeration and random walks, are used in community detection methods or in computation of centrality measures for…

Physics and Society · Physics 2015-03-20 J. K. Ochab

The rate of convergence of simple random walk on the Heisenberg group over $Z/nZ$ with a standard generating set was determined by Bump et al [1,2]. We extend this result to random walks on the same groups with an arbitrary minimal…

Probability · Mathematics 2016-07-20 Aaron Abrams , Henry Landau , Zeph Landau , James Pommersheim

Nearest neighbor random walks in the quarter plane that are absorbed when reaching the boundary are studied. The cases of positive and zero drift are considered. Absorption probabilities at a given time and at a given site are made…

Probability · Mathematics 2009-02-18 Kilian Raschel

In arbitrary spatial dimension $d\ge 1$, we study a generalized model of random walks in a time-varying random environment (RWRE) defined by a stochastic flow of kernels. We consider the quenched probability distribution of the random…

Probability · Mathematics 2025-10-28 Hindy Drillick , Shalin Parekh

In this paper we present a new and flexible method to show that, in one dimension, various self-repellent random walks converge to self-repellent Brownian motion in the limit of weak interaction after appropriate space-time scaling. Our…

Probability · Mathematics 2007-05-23 R. van der Hofstad , F. den Hollander , W. Koenig

An algorithm observes the trajectories of random walks over an unknown graph $G$, starting from the same vertex $x$, as well as the degrees along the trajectories. For all finite connected graphs, one can estimate the number of edges $m$ up…

Statistics Theory · Mathematics 2018-08-20 Anna Ben-Hamou , Roberto I. Oliveira , Yuval Peres

Lifted samplers form a class of Markov chain Monte Carlo methods which has drawn a lot attention in recent years due to superior performance in challenging Bayesian applications. A canonical example of lifted samplers is the one that is…

Computation · Statistics 2026-05-01 Philippe Gagnon , Florian Maire

Consider a generalized Elephant Random Walk in which the step is chosen by selecting $k$ previous steps with $k$ odd and then going in the majority direction with a probability $p$ and in the opposite direction otherwise. In the $k=1$ case…

Probability · Mathematics 2025-07-10 Simone Franchini

In the first part of this paper, we enumerate exactly walks on the square lattice that start from the origin, but otherwise avoid the non positive horizontal half-axis. We call them "walks on the slit plane". We count them by their length,…

Combinatorics · Mathematics 2025-09-26 Mireille Bousquet-Melou , Gilles Schaeffer

We study the asymptotic behaviour of a $d$-dimensional self-interacting random walk $X_n$ ($n = 1,2,...$) which is repelled or attracted by the centre of mass $G_n = n^{-1} \sum_{i=1}^n X_i$ of its previous trajectory. The walk's trajectory…

Probability · Mathematics 2011-06-21 Francis Comets , Mikhail V. Menshikov , Stanislav Volkov , Andrew R. Wade

We consider a Branching Random Walk on $\R$ whose step size decreases by a fixed factor, $0<b<1$, with each turn. This process generates a random probability measure on $\R$, that is, the limit of uniform distribution among the $2^n$…

Probability · Mathematics 2011-07-20 Itai Benjamini , Ori Gurel-Gurevich , Boris Solomyak

We numerically estimate the leading asymptotic behavior of the length $L_{n}$ of the longest increasing subsequence of random walks with step increments following Student's $t$-distribution with parameter in the range $1/2 \leq \nu \leq 5$.…

Statistical Mechanics · Physics 2020-03-11 J. Ricardo G. Mendonça , Hendrik Schawe , Alexander K. Hartmann

We present an analytical and numerical study of the paths of self avoiding walks (SAWs) on random networks. Since these walks do not retrace their paths, they effectively delete the nodes they visit, together with their links, thus pruning…

Disordered Systems and Neural Networks · Physics 2016-06-07 Ido Tishby , Ofer Biham , Eytan Katzav