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In this paper, we explore provable acceleration of diffusion models without any additional retraining. Focusing on the task of approximating a target data distribution in $\mathbb{R}^d$ to within $\varepsilon$ total-variation distance, we…

Machine Learning · Computer Science 2025-08-14 Gen Li , Yuchen Zhou , Yuting Wei , Yuxin Chen

In this paper we study the diffusion approximation of a swarming model given by a system of interacting Langevin equations with nonlinear friction. The diffusion approximation requires the calculation of the drift and diffusion coefficients…

Numerical Analysis · Mathematics 2015-05-08 V. Bonnaillie-Noël , J. A. Carrillo , T. Goudon , G. A. Pavliotis

Discrete diffusion models are a class of generative models that construct sequences by progressively denoising samples from a categorical noise distribution. Beyond their rapidly growing ability to generate coherent natural language, these…

Computation and Language · Computer Science 2025-12-11 Michael Cardei , Jacob K Christopher , Thomas Hartvigsen , Bhavya Kailkhura , Ferdinando Fioretto

We present an analytical study of the time dependent diffusion coefficient in a dilute suspension of spheres with partially absorbing boundary condition. Following Kirkpatrick (J. Chem. Phys. 76, 4255) we obtain a perturbative expansion for…

Statistical Mechanics · Physics 2012-10-29 Jiang Qian , Pabitra N. Sen

This paper presents a novel method for solving the 2D advection-diffusion equation using fixed-depth symbolic regression and symbolic differentiation without expression trees. The method is applied to two cases with distinct initial and…

Computation · Statistics 2024-11-12 Edward Finkelstein

Scale-free surfaces, such as cones, remain unchanged under a simultaneous expansion of all coordinates by the same factor. Probability density of a particle diffusing near such absorbing surface at large time approaches a simple form that…

Statistical Mechanics · Physics 2015-04-28 Nir Alfasi , Yacov Kantor

We study two-dimensional wave propagation in materials whose properties vary periodically in one direction only. High order homogenization is carried out to derive a dispersive effective medium approximation. One-dimensional materials with…

Numerical Analysis · Mathematics 2014-09-16 Manuel Quezada de Luna , David I. Ketcheson

To estimate the diffusion constant $D$ of particles in a plasma, we develop a method that is based on the mean free path $\lambda$ for scatterings with momentum transfer $q >~ T$. Using this method, we estimate $\lambda$ and $D$ for squarks…

High Energy Physics - Phenomenology · Physics 2009-10-31 Hooman Davoudiasl , Eric Westphal

To ensure the discrete maximum principle or solution positivity in finite volume schemes, diffusive flux is sometimes discretized as a conical combination of finite differences. Such a combination may be impossible to construct along…

Computational Physics · Physics 2015-06-19 D. Vidović , M. Dotlić , M. Pušić , B. Pokorni

Dispersion diagrams play a crucial role in examining, analyzing and designing wave propagation in periodic structures. Despite their ubiquity and current research interest, introductory papers and reference scripting tailored to novel…

Applied Physics · Physics 2024-04-19 Vanessa Cool , Elke Deckers , Lucas Van Belle , Claus Claeys

Explicit analytical expressions for the drag and diffusion coefficients of a spherical particle attached to the interface between two immiscible fluids are constructed for the case of a small viscosity ratio between the fluid phases. The…

Soft Condensed Matter · Physics 2016-04-20 Aaron Dörr , Steffen Hardt

Widely applicable, modified Green-Kubo expressions for the local diffusion coefficient ($D_l$) are obtained using linear response theory. In contrast to past definitions in use, these expressions are statistical mechanical results.…

Statistical Mechanics · Physics 2023-05-25 Michelle A. Hunter , Baris Demir , Charlotte F. Petersen , Debra J. Searles

We develop a dynamical formulation of one-dimensional scattering theory where the reflection and transmission amplitudes for a general, possibly complex and energy-dependent, scattering potential are given as solutions of a set of dynamical…

Quantum Physics · Physics 2015-06-17 Ali Mostafazadeh

Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation, and molecule design. In this survey, we provide an overview…

Machine Learning · Computer Science 2025-09-30 Ling Yang , Zhilong Zhang , Yang Song , Shenda Hong , Runsheng Xu , Yue Zhao , Wentao Zhang , Bin Cui , Ming-Hsuan Yang

Convection-diffusion equations provide the basis for describing heat and mass transfer phenomena as well as processes of continuum mechanics. To handle flows in porous media, the fundamental issue is to model correctly the convective…

Numerical Analysis · Computer Science 2012-08-29 A. Churbanov , P. Vabishchevich

Diffusion models have shown remarkable empirical success in sampling from rich multi-modal distributions. Their inference relies on numerically solving a certain differential equation. This differential equation cannot be solved in closed…

Machine Learning · Computer Science 2026-01-16 Khashayar Gatmiry , Sitan Chen , Adil Salim

Despite having been studied for decades, first passage processes remain an active area of research. In this contribution we examine a particle diffusing in an annulus with an inner absorbing boundary and an outer reflective boundary. We…

Statistical Mechanics · Physics 2022-10-05 Charles Antoine , Julian Talbot

In this work, the Z-average, effective, apparent diffusion coefficients and their poly-dispersity indexes were investigated for dilute poly-disperse homogeneous spherical particles in dispersion where the Rayleigh-Gans-Debye approximation…

Chemical Physics · Physics 2007-05-23 Yong Sun

Diffusion models, a family of generative models based on deep learning, have become increasingly prominent in cutting-edge machine learning research. With a distinguished performance in generating samples that resemble the observed data,…

Machine Learning · Computer Science 2023-05-02 Lequan Lin , Zhengkun Li , Ruikun Li , Xuliang Li , Junbin Gao

Diffusion model, the state-of-the-art generative machine learning architecture, has shown promising results airfoil inverse designs. In this study, we implemented and trained a series of diffusion models on three different airfoil geometry…

Fluid Dynamics · Physics 2026-01-26 Yingfan Geng , Jinhong Wang , Teng Cao
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