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In this paper we address the use of rare event computation techniques to estimate small over-threshold probabilities of observables in determin-istic dynamical systems. We demonstrate that the genealogical particle analysis algorithms can…

Statistical Mechanics · Physics 2016-09-21 Jeroen Wouters , Freddy Bouchet

Let $L$ be a linear differential operator acting on functions defined over an open set $\mathcal{D}\subset \mathbb{R}^d$. In this article, we characterize the measurable second order random fields $U = (U(x))_{x\in\mathcal{D}}$ whose sample…

Analysis of PDEs · Mathematics 2023-01-18 Iain Henderson , Pascal Noble , Olivier Roustant

Recent experimental studies on the stepwize motion of biological molecular motors have revealed that the ``characteristic distance'' of a step is usually less than the actual step size. This observation implies that the detailed-balance…

Statistical Mechanics · Physics 2009-11-11 Takahiro Harada , Naoko Nakagawa

Several important families of computational and statistical results in machine learning and randomized algorithms rely on uniform bounds on quadratic forms of random vectors or matrices. Such results include the Johnson-Lindenstrauss (J-L)…

Machine Learning · Computer Science 2019-12-06 Arindam Banerjee , Qilong Gu , Vidyashankar Sivakumar , Zhiwei Steven Wu

Let $B=(B_1(t),..,B_d(t))$ be a $d$-dimensional fractional Brownian motion with Hurst index $\alpha\le 1/4$, or more generally a Gaussian process whose paths have the same local regularity. Defining properly iterated integrals of $B$ is a…

Probability · Mathematics 2015-05-20 Jacques Magnen , Jérémie Unterberger

We bring the theory of rough paths to the study of non-parametric statistics on streamed data. We discuss the problem of regression where the input variable is a stream of information, and the dependent response is also (potentially) a…

Statistical Finance · Quantitative Finance 2016-03-23 Daniel Levin , Terry Lyons , Hao Ni

In this paper, the classical problem of the probabilistic characterization of a random variable is re-examined. A random variable is usually described by the probability density function (PDF) or by its Fourier transform, namely the…

Mathematical Physics · Physics 2013-01-22 Giulio Cottone , Mario Di Paola

The optimal transport (OT) map is a geometry-driven transformation between high-dimensional probability distributions which underpins a wide range of tasks in statistics, applied probability, and machine learning. However, existing…

Machine Learning · Statistics 2025-12-11 Sloan Nietert , Ziv Goldfeld

Fourier normal ordering \cite{Unt09bis} is a new algorithm to construct explicit rough paths over arbitrary H\"older-continuous multidimensional paths. We apply in this article the Fourier normal ordering ordering algorithm to the…

Probability · Mathematics 2009-06-08 Jeremie Unterberger

This article presents a general approximation-theoretic framework to analyze measure transport algorithms for probabilistic modeling. A primary motivating application for such algorithms is sampling -- a central task in statistical…

Numerical Analysis · Mathematics 2024-09-19 Ricardo Baptista , Bamdad Hosseini , Nikola B. Kovachki , Youssef M. Marzouk , Amir Sagiv

The restricted isometry property (RIP) is a well-known matrix condition that provides state-of-the-art reconstruction guarantees for compressed sensing. While random matrices are known to satisfy this property with high probability,…

Functional Analysis · Mathematics 2012-02-24 Afonso S. Bandeira , Matthew Fickus , Dustin G. Mixon , Percy Wong

Recently, Brandt, Maus and Uitto [PODC'19] showed that, in a restricted setting, the dependency of the complexity of the distributed Lov\'asz Local Lemma (LLL) on the chosen LLL criterion exhibits a sharp threshold phenomenon: They proved…

Data Structures and Algorithms · Computer Science 2020-06-09 Sebastian Brandt , Christoph Grunau , Václav Rozhoň

Many physical systems have underlying safety considerations that require that the policy employed ensures the satisfaction of a set of constraints. The analytical formulation usually takes the form of a Constrained Markov Decision Process…

Machine Learning · Computer Science 2021-03-03 Aria HasanzadeZonuzy , Archana Bura , Dileep Kalathil , Srinivas Shakkottai

A stochastic algorithm is proposed, finding the set of generalized means associated to a probability measure on a compact Riemannian manifold M and a continuous cost function on the product of M by itself. Generalized means include p-means…

Probability · Mathematics 2013-05-28 Marc Arnaudon , Laurent Miclo

For diffusive stochastic dynamics, the probability to observe any individual trajectory is vanishingly small, making it unclear how to experimentally validate theoretical results for ratios of path probabilities. We provide the missing link…

Statistical Mechanics · Physics 2021-08-04 Jannes Gladrow , Ulrich F. Keyser , R. Adhikari , Julian Kappler

The cutoff phenomenon was recently shown to systematically follow from non-negative curvature and the product condition, for all Markov diffusions. The proof crucially relied on a classical \emph{chain rule} satisfied by the carr\'e du…

Probability · Mathematics 2025-01-23 Francesco Pedrotti , Justin Salez

We consider a model of a quenched disordered geometry in which a random metric is defined on ${\mathbb R}^2$, which is flat on average and presents short-range correlations. We focus on the statistical properties of balls and geodesics,…

Statistical Mechanics · Physics 2015-06-09 Silvia N. Santalla , Javier Rodriguez-Laguna , Tom LaGatta , Rodolfo Cuerno

Rare events such as conformational changes in biomolecules, phase transitions, and chemical reactions are central to the behavior of many physical systems, yet they are extremely difficult to study computationally because unbiased…

Machine Learning · Statistics 2026-04-16 Yuanqi Du , Jiajun He , Dinghuai Zhang , Eric Vanden-Eijnden , Carles Domingo-Enrich

With recently developed tools, we prove a homogenisation theorem for a random ODE with short and long-range dependent fractional noise. The effective dynamics are not necessarily diffusions, they are given by stochastic differential…

Probability · Mathematics 2020-06-23 Johann Gehringer , Xue-Mei Li

We consider a finite sequence of random points in a finite domain of a finite-dimensional Euclidean space. The points are sequentially allocated in the domain according to a model of cooperative sequential adsorption. The main peculiarity…

Probability · Mathematics 2009-11-11 V. Shcherbakov
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