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In Lagrangian turbulence one is faced with the puzzle that 2D Navier-Stokes flows are nearly as intermittent as in three dimensions although no intermittency is present in the inverse cascade in 2D Eulerian turbulence. In addition, an…

Fluid Dynamics · Physics 2007-05-23 Rudolf Friedrich , Rainer Grauer , Holger Homann , Oliver Kamps

In this article, relying on Foster-Lyapunov drift conditions, we establish subexponential upper and lower bounds on the rate of convergence in the $\mathrm{L}^p$-Wasserstein distance for a class of irreducible and aperiodic Markov…

Probability · Mathematics 2022-02-28 Ari Arapostathis , Guodong Pang , Nikola Sandrić

Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyses often provide pessimistic convergence rates that do not reflect the intrinsic low-dimensional…

Machine Learning · Statistics 2026-04-24 Saptarshi Chakraborty , Quentin Berthet , Peter L. Bartlett

Score-based generative modeling, implemented through probability flow ODEs, has shown impressive results in numerous practical settings. However, most convergence guarantees rely on restrictive regularity assumptions on the target…

Machine Learning · Statistics 2025-10-21 Gitte Kremling , Francesco Iafrate , Mahsa Taheri , Johannes Lederer

We investigate the fractional diffusion approximation of a kinetic equation in the upper-half plane with diffusive reflection conditions at the boundary. In an appropriate singular limit corresponding to small Knudsen number and long time…

Analysis of PDEs · Mathematics 2019-09-04 Ludovic Cesbron , Antoine Mellet , Marjolaine Puel

We study the existence and the rate of equilibration of weak solutions to a two-component system of non-linear diffusion-aggregation equations, with small cross diffusion effects. The aggregation term is assumed to be purely attractive, and…

Analysis of PDEs · Mathematics 2024-06-17 Daniel Matthes , Christian Parsch

For a class of (non-symmetric) diffusion processes on a length space, which in particular include the (reflecting) diffusion processes on a connected compact Riemannian manifold, the exact convergence rate is derived for $({\mathbb E}…

Probability · Mathematics 2024-08-20 Feng-Yu Wang , Bingyao Wu , Jie-Xiang Zhu

\v{C}ech Persistence diagrams (PDs) are topological descriptors routinely used to capture the geometry of complex datasets. They are commonly compared using the Wasserstein distances $OT_{p}$; however, the extent to which PDs are stable…

Computational Geometry · Computer Science 2024-07-15 Charles Arnal , David Cohen-Steiner , Vincent Divol

Discretization of continuous-time diffusion processes is a widely recognized method for sampling. However, it seems to be a considerable restriction when the potentials are often required to be smooth (gradient Lipschitz). This paper…

Computation · Statistics 2022-02-23 Dao Nguyen

Numerous experimental and theoretical results in liquids and plasmas suggest the presence of a critical momentum at which the shear diffusion mode collides with a non-hydrodynamic relaxation mode, giving rise to propagating shear waves.…

High Energy Physics - Theory · Physics 2021-04-07 Matteo Baggioli

We are concerned with the well-posedness of an inverse problem for determining the wedge boundary and associated two-dimensional steady supersonic Euler flow past the wedge, provided that the pressure distribution on the boundary surface of…

Analysis of PDEs · Mathematics 2024-09-30 Gui-Qiang G. Chen , Yun Pu , Yongqian Zhang

The requirement of a non-negative dissipation rate for all possible deformation histories is generally imposed on plastic constitutive relations. This is a constraint analogous to the Coleman-Noll [1] postulate that the Clausius-Duhem…

Materials Science · Physics 2024-02-23 Alan Needleman

Underdamped Langevin dynamics (ULD) is a widely-used sampler for Gibbs distributions $\pi\propto e^{-V}$, and is often empirically effective in high dimensions. However, existing non-asymptotic convergence guarantees for discretized ULD…

Machine Learning · Computer Science 2026-03-04 Shiyuan Zhang , Qiwei Di , Xuheng Li , Quanquan Gu

Anomalous diffusion and L\'evy flights, which are characterized by the occurrence of random discrete jumps of all scales, have been observed in a plethora of natural and engineered systems, ranging from the motion of molecules to climate…

Dynamical Systems · Mathematics 2023-09-04 Chunxi Jiao , Georg A. Gottwald

We provide full theoretical guarantees for the convergence behaviour of diffusion-based generative models under the assumption of strongly log-concave data distributions while our approximating class of functions used for score estimation…

Machine Learning · Computer Science 2025-02-18 Stefano Bruno , Ying Zhang , Dong-Young Lim , Ömer Deniz Akyildiz , Sotirios Sabanis

Unbalanced probability circulation, which yields cyclic motions in phase space, is the defining characteristics of a stationary diffusion process without detailed balance. In over-damped soft matter systems, such behavior is a hallmark of…

Mathematical Physics · Physics 2015-09-22 Hong Qian

In a recent comment, M. Kosterlitz described how the discrepancy about the lack of broken translational symmetry in two dimensions - doubting the existence of 2D crystals - and the first computer simulations foretelling 2D crystals at least…

Statistical Mechanics · Physics 2017-03-27 Bernd Illing , Sebastian Frischi , Herbert Kaiser , Christian Klix , Georg Maret , Peter Keim

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 celebrated Sutherland-Einstein relation for systems at thermal equilibrium states that spread of trajectories of Brownian particles is an increasing function of temperature. Here, we scrutinize diffusion of underdamped Brownian motion…

Statistical Mechanics · Physics 2020-04-22 J. Spiechowicz , J. Luczka

Regression loss design is an essential topic for oriented object detection. Due to the periodicity of the angle and the ambiguity of width and height definition, traditional L1-distance loss and its variants have been suffered from the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Yuke Zhu , Yumeng Ruan , Zihua Xiong , Sheng Guo
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