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This paper studies sampling error bounds for denoising diffusion probabilistic models (DDPMs) in the 2-Wasserstein distance. Our contributions are threefold. (i) Under general Lipschitz-type conditions on the score function and for a broad…

Machine Learning · Statistics 2026-05-19 Yuta Koike

In many-particle diffusions, particles that move the furthest and fastest can play an outsized role in physical phenomena. A theoretical understanding of the behavior of such extreme particles is nascent. A classical model, in the spirit of…

Statistical Mechanics · Physics 2024-11-22 Jacob B. Hass , Aileen N. Carroll-Godfrey , Eric I. Corwin , Ivan Z. Corwin

We study Fredholm determinants related to a family of kernels which describe the edge eigenvalue behavior in unitary random matrix models with critical edge points. The kernels are natural higher order analogues of the Airy kernel and are…

Mathematical Physics · Physics 2009-01-19 T. Claeys , A. Its , I. Krasovsky

We formulate empirically the rapidity density distribution of produced particles in multiple particle production. The assumed mechanism is that the produced particles are emitted isotropically from several emitting centers, located on the…

High Energy Physics - Phenomenology · Physics 2010-09-21 A. Ohsawa , E. H. Shubuya , M. Tamada

Diffusion models have recently emerged as powerful tools for missing data imputation by modeling the joint distribution of observed and unobserved variables. However, existing methods, typically based on stochastic denoising diffusion…

Artificial Intelligence · Computer Science 2025-08-06 Youran Zhou , Mohamed Reda Bouadjenek , Sunil Aryal

The effect of introducing a mass dependent diffusion rate ~ m^{-alpha} in a model of coagulation with single-particle break up is studied both analytically and numerically. The model with alpha=0 is known to undergo a nonequilibrium phase…

Statistical Mechanics · Physics 2009-11-07 R. Rajesh , Dibyendu Das , Bulbul Chakraborty , Mustansir Barma

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

Time series forecasting models are becoming increasingly prevalent due to their critical role in decision-making across various domains. However, most existing approaches represent the coupled temporal patterns, often neglecting the…

Machine Learning · Computer Science 2025-09-26 Jintao Zhang , Mingyue Cheng , Xiaoyu Tao , Zhiding Liu , Daoyu Wang

The Totally Asymmetric Simple Exclusion Process (TASEP) is a non-equilibrium particle model on a finite one-dimensional lattice with open boundaries. In our earlier paper, we obtained a determinantal formula that computes the steady state…

Combinatorics · Mathematics 2015-03-09 Olya Mandelshtam

In recent advancements in high-fidelity image generation, Denoising Diffusion Probabilistic Models (DDPMs) have emerged as a key player. However, their application at high resolutions presents significant computational challenges. Current…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Jing Nathan Yan , Jiatao Gu , Alexander M. Rush

We consider the totally asymmetric simple exclusion process with initial conditions and/or jump rates such that shocks are generated. If the initial condition is deterministic, then the shock at time t will have a width of order t^{1/3}. We…

Mathematical Physics · Physics 2014-04-24 Patrik L. Ferrari , Peter Nejjar

We find the formulas of the transition probabilities of the $N$-particle multi-species asymmetric simple exclusion processes (ASEP), and show that the transition probabilities are written as a determinant when the order of particles in the…

Mathematical Physics · Physics 2020-12-22 Eunghyun Lee

We give the distribution function of $M_n$, the maximum of a sequence of $n$ observations from an autoregressive process of order 2. Solutions are first given in terms of repeated integrals and then for the case, where the underlying random…

Statistics Theory · Mathematics 2010-02-02 C. S. Withers , S. Nadarajah

We construct an estimator of the unknown drift parameter $\theta\in {\mathbb{R}}$ in the linear model \[X_t=\theta t+\sigma_1B^{H_1}(t)+\sigma_2B^{H_2}(t),\;t\in[0,T],\] where $B^{H_1}$ and $B^{H_2}$ are two independent fractional Brownian…

Probability · Mathematics 2015-08-13 Yuliya Mishura , Ivan Voronov

We address the multiple testing problem under the assumption that the true/false hypotheses are driven by a Hidden Markov Model (HMM), which is recognized as a fundamental setting to model multiple testing under dependence since the seminal…

Methodology · Statistics 2021-05-04 Marie Perrot-Dockès , Gilles Blanchard , Pierre Neuvial , Etienne Roquain

The time it takes the fastest searcher out of $N\gg1$ searchers to find a target determines the timescale of many physical, chemical, and biological processes. This time is called an extreme first passage time (FPT) and is typically much…

Probability · Mathematics 2019-12-10 Sean D Lawley

Diffusion can be conceptualized, at microscopic scales, as the random hopping of particles between neighboring lattice sites. In the case of diffusion in inhomogeneous media, distinct spatial domains in the system may yield distinct…

Biological Physics · Physics 2017-10-02 Yiwei Li , Osman Kahraman , Christoph A. Haselwandter

The exclusion process in which particles may jump any distance l>=1 with the probability that decays as l^-(1+sigma) is studied from coarse-grained equation for density profile in the limit when the lattice spacing goes to zero. For…

Statistical Mechanics · Physics 2008-05-16 J. Szavits-Nossan , K. Uzelac

Denoising Diffusion Probabilistic Models (DDPMs) are a very popular class of deep generative model that have been successfully applied to a diverse range of problems including image and video generation, protein and material synthesis,…

We determine the propagation properties of a quantum particle in a d-dimensional lattice with hopping disorder, delta-correlated in time. The system is delocalized: the averaged transition probability shows a diffusive behavior. Then,…

Statistical Mechanics · Physics 2007-05-23 G. C. Ferrario , V. G. Benza