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Consider a discrete uniformly elliptic divergence form equation on the $d$ dimensional lattice $\Z^d$ with random coefficients. It has previously been shown that if the random environment is translational invariant, then the averaged…

Analysis of PDEs · Mathematics 2011-01-26 Joseph G. Conlon , Thomas Spencer

We review various characterizations of uniform convexity and smoothness on norm balls in finite-dimensional spaces and connect results stemming from the geometry of Banach spaces with \textit{scaling inequalities} used in analysing the…

Optimization and Control · Mathematics 2021-02-19 Thomas Kerdreux , Alexandre d'Aspremont , Sebastian Pokutta

Equations that follow from the Navier-Stokes equation and incompressibility but with no other approximations are called "exact" here. Exact equations relating 2nd and 3rd-order structure functions are obtained, as is an exact…

Fluid Dynamics · Physics 2007-05-23 Reginald J. Hill

Diffusion models accomplish remarkable success in data generation tasks across various domains. However, the iterative sampling process is computationally expensive. Consistency models are proposed to learn consistency functions to map from…

Machine Learning · Computer Science 2025-05-07 Yiding Chen , Yiyi Zhang , Owen Oertell , Wen Sun

In this paper, we consider the well known problem of estimating a density function under qualitative assumptions. More precisely, we estimate monotone non increasing densities in a Bayesian setting and derive concentration rate for the…

Statistics Theory · Mathematics 2015-02-20 Jean-Bernard Salomond

We investigate the evaporation of a two-dimensional droplet on a solid surface. The solid is flat but with smooth chemical variations that lead to a space-dependent local contact angle. We perform a detailed bifurcation analysis of the…

Fluid Dynamics · Physics 2021-03-31 Michael Ewetola , Rodrigo Ledesma-Aguilar , Marc Pradas

We study lower and upper bounds for the density of a diffusion process in ${\mathbb{R}}^n$ in a small (but not asymptotic) time, say $\delta$. We assume that the diffusion coefficients $\sigma_1,\ldots,\sigma_d$ may degenerate at the…

Probability · Mathematics 2019-12-03 Vlad Bally , Lucia Caramellino , Paolo Pigato

Motivated by the normal form of a fast-slow ordinary differential equation exhibiting a pitchfork singularity we consider the discrete-time dynamical system that is obtained by an application of the explicit Euler method. Tracking…

Dynamical Systems · Mathematics 2019-11-22 Luca Arcidiacono , Maximilian Engel , Christian Kuehn

This paper is devoted to the multigrid convergence analysis for the linear systems arising from the conforming linear finite element discretization of the second order elliptic equations with anisotropic diffusion. The multigrid convergence…

Numerical Analysis · Mathematics 2011-05-09 Guozhu Yu , Jinchao Xu , Ludmil Zikatanov

Diffusive dynamics in presence of deep energy minima and weak nongradient forces can be coarse-grained into a mesoscopic jump process over the various basins of attraction. Combining standard weak-noise results with a path integral…

Statistical Mechanics · Physics 2021-04-14 Gianmaria Falasco , Massimiliano Esposito

Optimization problems involving the minimization of a finite sum of smooth, possibly non-convex functions arise in numerous applications. To achieve a consensus solution over a network, distributed optimization algorithms, such as…

Optimization and Control · Mathematics 2025-07-09 Lei Qin , Ye Pu

This paper considers approximate smoothing for discretely observed non-linear stochastic differential equations. The problem is tackled by developing methods for linearising stochastic differential equations with respect to an arbitrary…

Methodology · Statistics 2019-01-21 Filip Tronarp , Simo Särkkä

We consider in this work small random perturbations (of multiplicative noise type) of the gradient flow. We prove that under mild conditions, when the potential function is a Morse function with additional strong saddle condition, the…

Probability · Mathematics 2020-04-29 Jiaojiao Yang , Wenqing Hu , Chris Junchi Li

The notion of statistical depth has been extensively studied in multivariate and functional data over the past few decades. In contrast, the depth on temporal point process is still under-explored. The problem is challenging because a point…

Methodology · Statistics 2021-05-24 Zishen Xu , Chenran Wang , Wei Wu

This paper studies system theoretic properties of the class of difference inclusions of convex processes. We will develop a framework considering eigenvalues and eigenvectors, weakly and strongly invariant cones, and a decomposition of…

Optimization and Control · Mathematics 2021-12-30 Jaap Eising , M. Kanat Camlibel

A proof of convergence is given for semi- and full discretizations of mean curvature flow of closed two-dimensional surfaces. The numerical method proposed and studied here combines evolving finite elements, whose nodes determine the…

Numerical Analysis · Mathematics 2019-06-27 Balázs Kovács , Buyang Li , Christian Lubich

We develop and extend a method presented in [S. Patinet, D. Vandembroucq, and M. L. Falk, Phys. Rev. Lett., 117, 045501 (2016)] to compute the local yield stresses at the atomic scale in model two-dimensional Lennard-Jones glasses produced…

This paper presents some limit theorems for certain functionals of moving averages of semimartingales plus noise which are observed at high frequency. Our method generalizes the pre-averaging approach (see [Bernoulli 15 (2009) 634--658,…

Statistics Theory · Mathematics 2010-10-05 Jean Jacod , Mark Podolskij , Mathias Vetter

We discuss relaxation and aging processes in the one- and two-dimensional $ABC$ models. In these driven diffusive systems of three particle types, biased exchanges in one direction yield a coarsening process characterized in the long time…

Statistical Mechanics · Physics 2015-05-13 Mark O. Brown , Robert H. Galyean , Xiangwen Wang , Michel Pleimling

Gradient normalization and soft clipping are two popular techniques for tackling instability issues and improving convergence of stochastic gradient descent (SGD) with momentum. In this article, we study these types of methods through the…

Optimization and Control · Mathematics 2025-07-01 Måns Williamson , Tony Stillfjord