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Diffusion models are one of the most important families of deep generative models. In this note, we derive a quantitative upper bound on the Wasserstein distance between the data-generating distribution and the distribution learned by a…

Machine Learning · Computer Science 2024-09-17 Sokhna Diarra Mbacke , Omar Rivasplata

We analyze the posterior contraction rates of parameters in Bayesian models via the Langevin diffusion process, in particular by controlling moments of the stochastic process and taking limits. Analogous to the non-asymptotic analysis of…

Statistics Theory · Mathematics 2022-08-18 Wenlong Mou , Nhat Ho , Martin J. Wainwright , Peter Bartlett , Michael I. Jordan

Understanding the macroscopic characteristics of biological complexes demands precision and specificity in statistical ensemble modeling. One of the primary challenges in this domain lies in sampling from particular subsets of the…

Machine Learning · Computer Science 2023-07-11 Justin Diamond , Markus Lill

Front propagation in time dependent laminar flows is investigated in the limit of very fast reaction and very thin fronts, i.e. the so-called geometrical optics limit. In particular, we consider fronts evolving in time correlated random…

Chaotic Dynamics · Physics 2009-11-11 M. Chinappi , M. Cencini , A. Vulpiani

This work is an extended version of the paper arXiv:0803.2669v1[math-ph], in which the main results were announced. We consider certain classical diffusion process for a wave function on the phase space. It is shown that at the time of…

Mathematical Physics · Physics 2008-12-31 E. M. Beniaminov

In this paper, we are interested in a generalised Vlasov equation, which describes the evolution of the probability density of a particle evolving according to a generalised Vlasov dynamic. The achievement of the paper is twofold. Firstly,…

Analysis of PDEs · Mathematics 2015-01-14 Manh Hong Duong

The exponential contraction in $L^1$-Wasserstein distance and exponential convergence in $L^q$-Wasserstein distance ($q\geq 1$) are considered for stochastic differential equations with irregular drift. When the irregular drift drift is…

Probability · Mathematics 2024-04-22 Shao-Qin Zhang

We develop a projected Wasserstein distance for the two-sample test, a fundamental problem in statistics and machine learning: given two sets of samples, to determine whether they are from the same distribution. In particular, we aim to…

Machine Learning · Statistics 2024-04-01 Jie Wang , Rui Gao , Yao Xie

Consider a graph where the sites are distributed in space according to a Poisson point process on $\mathbb R^n$. We study a population evolving on this network, with individuals jumping between sites with a rate which decreases…

Probability · Mathematics 2023-04-05 Vincent Bansaye , Michele Salvi

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

We consider a one-dimensional diffusion process $(X_t)$ which is observed at $n+1$ discrete times with regular sampling interval $\Delta$. Assuming that $(X_t)$ is strictly stationary, we propose nonparametric estimators of the drift and…

Statistics Theory · Mathematics 2009-09-29 Fabienne Comte , Valentine Genon-Catalot , Yves Rozenholc

In this paper we investigate the porous medium equation with a fractional temporal derivative. We justify that the resulting equation emerges when we consider the waiting-time (or trapping) phenomenon that can happen in the medium. Our…

Analysis of PDEs · Mathematics 2015-05-20 Łukasz Płociniczak

We consider processes that coincide with a given diffusion process outside a finite collection of domains. In each of the domains, there is, additionally, a large drift directed towards the interior of the domain. We describe the limiting…

Probability · Mathematics 2015-10-20 Mark Freidlin , Leonid Koralov , Alexander Wentzell

We assume that we observe $N$ independent copies of a diffusion process on a time-interval $[0,2T]$. For a given time $t$, we estimate the transition density $p_t(x,y)$, namely the conditional density of $X_{t + s}$ given $X_s = x$, under…

Statistics Theory · Mathematics 2025-05-01 Fabienne Comte , Nicolas Marie

This paper is concerned with stochastic processes that model multiple (or iterated) scattering in classical mechanical systems of billiard type, defined below. From a given (deterministic) system of billiard type, a random process with…

Mathematical Physics · Physics 2015-06-11 Renato Feres , Jasmine Ng , Hong-Kun Zhang

The problem of modeling the relationship between univariate distributions and one or more explanatory variables has found increasing interest. Traditional functional data methods cannot be applied directly to distributional data because of…

Methodology · Statistics 2025-02-04 Yidong Zhou , Hans-Georg Müller

A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. The fundamental solution (for the…

Statistical Mechanics · Physics 2007-09-25 Rudolf Gorenflo , Francesco Mainardi , Daniele Moretti , Gianni Pagnini , Paolo Paradisi

This paper is devoted to the study of the following problem. We have set of diffusion processes with absorption on boundaries in some region at initial time $t=0$. It is required to estimate of number of the unabsorbed processes for the…

Probability · Mathematics 2007-05-23 Anielllo Fedullo , Vitalii A. Gasanenko

We introduce a framework for generating samples of a distribution given a finite number of its moments, targeted to particle-based solutions of kinetic equations and rarefied gas flow simulations. Our model, referred to as the…

Computational Physics · Physics 2023-08-08 Mohsen Sadr , Nicolas G. Hadjiconstantinou , M. Hossein Gorji

The diffusion of finite-size hard-core interacting particles in two- or three-dimensional confined domains is considered in the limit that the confinement dimensions become comparable to the particle's dimensions. The result is a nonlinear…

Mathematical Physics · Physics 2017-03-23 Maria Bruna , S. Jonathan Chapman