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Discrete time random walks, in which a step of random sign but constant length $\delta x$ is performed after each time interval $\delta t$, are widely used models for stochastic processes. In the case of a correlated random walk, the next…

Quantitative Methods · Quantitative Biology 2012-07-11 F. Stadler , C. Metzner , J. Steinwachs , B. Fabry

Dirichlet Process mixture models (DPMM) in combination with Gaussian kernels have been an important modeling tool for numerous data domains arising from biological, physical, and social sciences. However, this versatility in applications…

Statistics Theory · Mathematics 2023-01-30 Aritra Guha , Nhat Ho , XuanLong Nguyen

We establish inequalities for assessing the distance between the distribution of a (possibly multidimensional) functional of a Poisson random measure and that of a Gaussian element. Our bounds only involve add-one cost operators at the…

Probability · Mathematics 2020-10-27 Raphaël Lachièze-Rey , Giovanni Peccati , Xiaochuan Yang

Gaussian processes scale prohibitively with the size of the dataset. In response, many approximation methods have been developed, which inevitably introduce approximation error. This additional source of uncertainty, due to limited…

Machine Learning · Computer Science 2023-10-11 Jonathan Wenger , Geoff Pleiss , Marvin Pförtner , Philipp Hennig , John P. Cunningham

The far-from-equilibrium dynamics of glassy systems share important phenomenological traits. A transition is generally observed from a time-homogeneous dynamical regime to an aging regime where physical changes occur intermittently and, on…

Soft Condensed Matter · Physics 2015-03-13 S. Boettcher , P. Sibani

A strategy is developed for generating equilibrated high molecular-weight polymer melts described with microscopic detail by sequentially backmapping coarse-grained (CG) configurations. The microscopic test model is generic but retains…

Soft Condensed Matter · Physics 2016-10-25 Guojie Zhang , Livia A. Moreira , Torsten Stuehn , Kostas Ch. Daoulas , Kurt Kremer

Uncovering genuine relationships between a response variable of interest and a large collection of covariates is a fundamental and practically important problem. In the context of Gaussian linear models, both the Bayesian and non-Bayesian…

Statistics Theory · Mathematics 2025-04-11 Jeyong Lee , Minwoo Chae , Ryan Martin

Gaussian smoothed sliced Wasserstein distance has been recently introduced for comparing probability distributions, while preserving privacy on the data. It has been shown that it provides performances similar to its non-smoothed…

Machine Learning · Computer Science 2024-04-26 Mokhtar Z. Alaya , Alain Rakotomamonjy , Maxime Berar , Gilles Gasso

The current status of implementing Tsallis (nonextensive) statistics on high-energy physics is briefly reviewed. The remarkably low freezeout-temperature, which apparently fails to reproduce the first-principle lattice QCD thermodynamics…

High Energy Physics - Phenomenology · Physics 2018-04-30 Abdel Nasser Tawfik

Unless constrained by symmetry, measurement of an observable on an ensemble of identical quantum systems returns a distribution of values which are encoded in the full counting statistics. While the mean value of this distribution is…

Statistical Mechanics · Physics 2024-04-03 David X. Horvath , Colin Rylands

Macroscopic mechanical properties of polymers are determined by their microscopic molecular chain distribution. Due to randomness of these molecular chains, probability theory has been used to find their micro-states and energy…

Statistical Mechanics · Physics 2023-08-23 Lixiang Yang

We develop a unified scaling framework for the end-position distributions of tethered polymers confined in finite cylindrical geometries. Two observables are analysed: the longitudinal distribution P(x), along the confinement axis, and the…

Soft Condensed Matter · Physics 2025-12-16 Bibhatsu Kuiri , Rittwick Mondal , Dipankar Biswas , Soumyajyoti Kabi

Based on non-equilibrium molecular dynamics simulations of entangled polymer melts, a recent Letter [Phys. Rev. Lett. $\textbf{121}$, 047801 (2018), arXiv:1806.09509] claims that the rising extensional stress is quantitatively consistent…

Soft Condensed Matter · Physics 2019-02-13 Wen-Sheng Xu , Christopher N. Lam , Jan-Michael Y. Carrillo , Bobby G. Sumpter , Yangyang Wang

Parallel-tempering MD results for a CH$_3$(CH$_2$-O-CH$_2$)$_m$CH$_3$ chain in water are exploited as a data-base for analysis of collective structural characteristics of the PEO globule with a goal of defining models permitting statistical…

Chemical Physics · Physics 2014-04-29 M. I. Chaudhari , L. R. Pratt , M. E. Paulaitis

The reconstruction of galaxy cluster's gas density profiles is usually performed by assuming spherical symmetry and averaging the observed X-ray emission in circular annuli. In the case of a very inhomogeneous and asymmetric gas…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-15 D. Eckert , M. Roncarelli , S. Ettori , S. Molendi , F. Vazza , F. Gastaldello , M. Rossetti

This paper considers the posterior contraction of non-parametric Bayesian inference on non-homogeneous Poisson processes. We consider the quality of inference on a rate function $\lambda$, given non-identically distributed realisations,…

Statistics Theory · Mathematics 2019-06-26 James A. Grant , David S. Leslie

We propose a novel combinatorial algorithm for efficient generation of Hamiltonian walks and cycles on a cubic lattice, modeling the conformations of lattice toy proteins. Through extensive tests on small lattices (allowing complete…

Soft Condensed Matter · Physics 2007-05-23 Rhonald Lua , Alexander L. Borovinskiy , Alexander Yu. Grosberg

We present a statistical model of a dilute polymer solution in good solvent in the presence of low-molecular weight cosolvent. We investigate the conformational changes of the polymer induced by a change of the cosolvent concentration and…

Statistical Mechanics · Physics 2014-11-10 Yu. A. Budkov , A. L. Kolesnikov , N. Georgi , M. G. Kiselev

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský

Gaussian Process regression is a kernel method successfully adopted in many real-life applications. Recently, there is a growing interest on extending this method to non-Euclidean input spaces, like the one considered in this paper,…

Machine Learning · Computer Science 2022-12-05 Antonio Candelieri , Andrea Ponti , Francesco Archetti