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The paper is concerned with the finite element solution of the Poisson equation with homogeneous Dirichlet boundary condition in a three-dimensional domain. Anisotropic, graded meshes from a former paper are reused for dealing with the…

Numerical Analysis · Mathematics 2019-02-20 Thomas Apel , Ariel L. Lombardi , Max Winkler

Inspired by the chemical etching processes, where experiments show that growth rates depending on the local environment might play a fundamental role in determining the properties of the etched surfaces, we study here a model for kinetic…

Statistical Mechanics · Physics 2007-05-23 Raffaele Cafiero

The finite-element method is a preferred numerical method when electromagnetic fields at high accuracy are to be computed in nano-optics design. Here, we demonstrate a finite-element method using hp-adaptivity on tetrahedral meshes for…

In this paper we address the convergence of stochastic approximation when the functions to be minimized are not convex and nonsmooth. We show that the "mean-limit" approach to the convergence which leads, for smooth problems, to the ODE…

Optimization and Control · Mathematics 2018-05-08 Szymon Majewski , Błażej Miasojedow , Eric Moulines

This article introduces a general statistical modeling principle called "Density Sharpening" and applies it to the analysis of discrete count data. The underlying foundation is based on a new theory of nonparametric approximation and…

Methodology · Statistics 2021-08-24 Subhadeep Mukhopadhyay

Heterogeneous materials exhibit anisotropy which is influenced by factors such as individual phase properties and microstructural configuration that form crucial descriptors of heterogeneity. A review of anisotropy indices proposed in the…

Materials Science · Physics 2025-04-15 Abhilash M Nagaraja

One of the principal difficulties in stochastic homogenization is transferring quantitative ergodic information from the coefficients to the solutions, since the latter are nonlocal functions of the former. In this paper, we address this…

Analysis of PDEs · Mathematics 2017-06-07 Scott Armstrong , Tuomo Kuusi , Jean-Christophe Mourrat

In this paper, we use a unified framework introduced in [3] to study two classes of nonconforming immersed finite element (IFE) spaces with integral value degrees of freedom. The shape functions on interface elements are piecewise…

Numerical Analysis · Mathematics 2018-10-19 Ruchi Guo , Tao Lin , Xu Zhang

Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Unfortunately, the nature of this approximation result is…

Statistics Theory · Mathematics 2020-08-24 T Tin Nguyen , Hien D Nguyen , Faicel Chamroukhi , Geoffrey J McLachlan

We propose a simple and efficient scheme based on adaptive finite elements over conforming quadtree meshes for collapse plastic analysis of structures. Our main interest in kinematic limit analysis is concerned with both purely…

Computational Engineering, Finance, and Science · Computer Science 2019-03-11 H Nguyen-Xuan , Hien V Do , Khanh N Chau

In this paper, we introduce a method known as polynomial frame approximation for approximating smooth, multivariate functions defined on irregular domains in $d$ dimensions, where $d$ can be arbitrary. This method is simple, and relies only…

Numerical Analysis · Mathematics 2020-05-27 Ben Adcock , Daan Huybrechs

We study extremal curves associated with a functional which is linear in the curve's torsion. The functional in question is known to capture the properties of entanglement entropy for two-dimensional conformal field theories with chiral…

High Energy Physics - Theory · Physics 2018-08-29 Piermarco Fonda , Diego Liska , Alvaro Veliz-Osorio

Sloppy models are complex nonlinear models with outcomes that are significantly affected by only a small subset of parameter combinations. Despite forming an important universality class and arising frequently in practice, formal and…

Numerical Analysis · Mathematics 2019-04-24 Katherine N. Quinn , Heather Wilber , Alex Townsend , James P. Sethna

We develop a new approach to characterizing the morphology of rough surfaces based on the analysis of the scaling properties of contour loops, i.e. loops of constant height. Given a height profile of the surface we perform independent…

Materials Science · Physics 2009-10-31 J. Kondev , C. L. Henley , D. G. Salinas

The paper considers functional linear regression, where scalar responses $Y_1,...,Y_n$ are modeled in dependence of random functions $X_1,...,X_n$. We propose a smoothing splines estimator for the functional slope parameter based on a…

Statistics Theory · Mathematics 2009-02-26 Christophe Crambes , Alois Kneip , Pascal Sarda

Statistical Shape Modeling (SSM) is a quantitative method for analyzing morphological variations in anatomical structures. These analyses often necessitate building models on targeted anatomical regions of interest to focus on specific…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Hong Xu , Alan Morris , Shireen Y. Elhabian

Advancements in modern semiconductor devices increasingly depend on the utilization of amorphous materials and the reduction of material thickness, pushing the boundaries of their physical capabilities. The mechanical properties of these…

Applied Physics · Physics 2024-05-31 C. Pashartis , M. J. van Setten , M. Houssa , G. Pourtois

Using a particle model of Physarum displaying emer- gent morphological adaptation behaviour we demonstrate how a minimal approach to collective material computation may be used to transform and summarise properties of spatially represented…

Emerging Technologies · Computer Science 2015-03-12 Jeff Jones , Andrew Adamatzky

An unbiased estimator for the ellipticity of an object in a noisy image is given in terms of the image moments. Three assumptions are made: i) the pixel noise is normally distributed, although with arbitrary covariance matrix, ii) the image…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-09 Nicolas Tessore

Choosing the optimization algorithm that performs best on a given machine learning problem is often delicate, and there is no guarantee that current state-of-the-art algorithms will perform well across all tasks. Consequently, the more…

Optimization and Control · Mathematics 2024-06-25 Måns Williamson , Monika Eisenmann , Tony Stillfjord