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We develop a unified approach to defining a point at infinity for an arbitrary space and formalizing convergence to this point. Central to our work is a method to quantify and classify the rates at which functions approach their limits at…

Functional Analysis · Mathematics 2025-12-16 Armen Petrosyan

We initiate a program of average smoothness analysis for efficiently learning real-valued functions on metric spaces. Rather than using the Lipschitz constant as the regularizer, we define a local slope at each point and gauge the function…

Statistics Theory · Mathematics 2020-11-10 Yair Ashlagi , Lee-Ad Gottlieb , Aryeh Kontorovich

Given a function f defined on a bidimensional bounded domain and a positive integer N, we study the properties of the triangulation that minimizes the distance between f and its interpolation on the associated finite element space, over all…

Numerical Analysis · Mathematics 2012-06-06 Jean-Marie Mirebeau

We address composite optimization problems, which consist in minimizing the sum of a smooth and a merely lower semicontinuous function, without any convexity assumptions. Numerical solutions of these problems can be obtained by proximal…

Optimization and Control · Mathematics 2024-02-14 Alberto De Marchi

Functional data analysis almost always involves smoothing discrete observations into curves, because they are never observed in continuous time and rarely without error. Although smoothing parameters affect the subsequent inference,…

Methodology · Statistics 2025-04-07 Sunny G. W. Wang , Valentin Patilea , Nicolas Klutchnikoff

We introduce meshfree finite difference methods for approximating nonlinear elliptic operators that depend on second directional derivatives or the eigenvalues of the Hessian. Approximations are defined on unstructured point clouds, which…

Numerical Analysis · Mathematics 2017-05-03 Brittany D. Froese

Probability density estimation is a core problem of statistics and signal processing. Moment methods are an important means of density estimation, but they are generally strongly dependent on the choice of feasible functions, which severely…

Machine Learning · Statistics 2023-07-06 Guangyu Wu , Anders Lindquist

We propose an approach to measure surface elastic constants of soft solids. Generally, this requires one to probe interfacial mechanics at around the elastocapillary length scale, which is typically microscopic. Deformations of microscopic…

Soft Condensed Matter · Physics 2022-03-02 Stefanie Heyden , Petia M. Vlahovska , Eric R. Dufresne

We study the fluid-mediated approach of a deformable axisymmetric object towards a rigid substrate, focusing on how its shape influences contact formation. For low approach velocities and large Stokes numbers, we show that sharper profiles…

Soft Condensed Matter · Physics 2025-10-21 Joaquin Garcia-Suarez

In this paper, we introduce a multiscale framework based on adaptive edge basis functions to solve second-order linear elliptic PDEs with rough coefficients. One of the main results is that we prove the proposed multiscale method achieves…

Numerical Analysis · Mathematics 2021-08-19 Yifan Chen , Thomas Y. Hou , Yixuan Wang

While isotropic in-plane swelling problems for thin elastic sheets have been studied extensively in recent years, many shape-programmable materials, including nematic solids and 3D-printed structures, are anisotropic, as are most industrial…

Soft Condensed Matter · Physics 2021-05-25 H. G. Wood , J. A. Hanna

In this paper, we propose crossing statistics and its generalization, as a new framework to characterize the anisotropy in a 2D field, e.g. height on a surface, extendable to higher dimensions. By measuring $\nu^+$, the number of…

Computational Physics · Physics 2018-10-12 M. Ghasemi Nezhadhaghighi , S. M. S. Movahed , T. Yasseri , S. M. Vaez Allaei

Given a data set (t_i, y_i), i=1,..., n with the t_i in [0,1] non-parametric regression is concerned with the problem of specifying a suitable function f_n:[0,1] -> R such that the data can be reasonably approximated by the points (t_i,…

Methodology · Statistics 2009-03-18 P. L. Davies , M. Meise

We describe and analyze algorithms for shape-constrained symbolic regression, which allows the inclusion of prior knowledge about the shape of the regression function. This is relevant in many areas of engineering -- in particular whenever…

Neural and Evolutionary Computing · Computer Science 2021-07-21 Christian Haider , Fabricio Olivetti de França , Bogdan Burlacu , Gabriel Kronberger

We address the problem of learning an unknown smooth function and its derivatives from noisy pointwise evaluations under the supremum norm. While classical nonparametric regression provides a strong theoretical foundation, traditional…

Machine Learning · Computer Science 2026-03-10 Davide Maran , Marcello Restelli

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

A mesoscopic model for shear plasticity of amorphous materials in two dimensions is introduced, and studied through numerical simulations in order to elucidate the macroscopic (large scale) mechanical behavior. Plastic deformation is…

Soft Condensed Matter · Physics 2012-05-17 Mehdi Talamali , Viljo Petäjä , Damien Vandembroucq , Stéphane Roux

Parametric max-stable processes are increasingly used to model spatial extremes. Starting from the fact that the dependence structure of a max-stable process is completely characterized by an extreme-value copula, a class of goodness-of-fit…

Methodology · Statistics 2015-02-27 Ivan Kojadinovic , Hongwei Shang , Jun Yan

We define a regularized size-shape distortion (quality) measure for curved high-order elements on a Riemannian space. To this end, we measure the deviation of a given element, straight-sided or curved, from the stretching, alignment, and…

Computational Engineering, Finance, and Science · Computer Science 2024-03-21 Guillermo Aparicio-Estrems , Abel Gargallo-Peiró , Xevi Roca

Affine deformations serve as basic examples in the continuum mechanics of deformable 3-dimensional bodies (referred as homogeneous deformations). They preserve parallelism and are often used as an approximation to general deformations.…

Differential Geometry · Mathematics 2015-08-03 N. Kadianakis , F. I. Travlopanos
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