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A trigonometric interpolation algorithm for non-periodic functions has been recently proposed and applied to study general ordinary differential equation (ODE). This paper enhances the algorithm to approximate functions in $2$-dim space.…

Numerical Analysis · Mathematics 2025-08-14 Xiaorong Zou

We present an a posteriori error analysis for the mixed virtual element method (mixed VEM) applied to second order elliptic equations in divergence form with mixed boundary conditions. The resulting error estimator is of residual-type. It…

Numerical Analysis · Mathematics 2019-04-24 Andrea Cangiani , Mauricio Munar

The Generalized Finite Element Method (GFEM) is a Partition of Unity Method (PUM), where the trial space of standard Finite Element Method (FEM) is augmented with non-polynomial shape functions with compact support. These shape functions,…

Numerical Analysis · Mathematics 2015-05-27 I. Babuska , U. Banerjee

We study in this paper the function approximation error of multivariate linear extrapolation. The sharp error bound of linear interpolation already exists in the literature. However, linear extrapolation is used far more often in…

Optimization and Control · Mathematics 2026-05-20 Liyuan Cao , Zaiwen Wen , Ya-xiang Yuan

Motivated by the successful use of greedy algorithms for Reduced Basis Methods, a greedy method is proposed that selects N input data in an asymptotically optimal way to solve well-posed operator equations using these N data. The operator…

Numerical Analysis · Mathematics 2019-03-28 Robert Schaback

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

We consider interpolation learning in high-dimensional linear regression with Gaussian data, and prove a generic uniform convergence guarantee on the generalization error of interpolators in an arbitrary hypothesis class in terms of the…

Machine Learning · Statistics 2022-01-05 Frederic Koehler , Lijia Zhou , Danica J. Sutherland , Nathan Srebro

In this paper, we extend the Generalized Finite Difference Method (GFDM) on unknown compact submanifolds of the Euclidean domain, identified by randomly sampled data that (almost surely) lie on the interior of the manifolds. Theoretically,…

Numerical Analysis · Mathematics 2023-07-18 Shixiao W. Jiang , Rongji Li , Qile Yan , John Harlim

Given $E_0, E_1, E, F$ rearrangement invariant spaces, $a, b, b_0, b_1$ slowly varying functions and $0\leq \theta_0<\theta_1\leq 1$, we characterize the interpolation space $$(\overline{X}_{\theta_0,b_0,E_0}, \overline{X}^{\mathcal…

Functional Analysis · Mathematics 2020-10-15 Pedro Fernández-Martínez , Teresa M. Signes

Data-dependent greedy algorithms in kernel spaces are known to provide fast converging interpolants, while being extremely easy to implement and efficient to run. Despite this experimental evidence, no detailed theory has yet been…

Numerical Analysis · Mathematics 2022-10-31 Tizian Wenzel , Gabriele Santin , Bernard Haasdonk

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

Using Gabor analysis, we give a complete characterization of all lattice sampling and interpolating sequences in the Fock space of polyanalytic functions, displaying a "Nyquist rate" which increases with $n$, the degree of polyanaliticity…

Functional Analysis · Mathematics 2009-12-02 Luis Daniel Abreu

Genome-Scale Metabolic Models (GEMs) describe the interactions between genes, proteins, and the biochemical reactions that underpin an organism's metabolism aiming to computationally simulate functions at the cellular level. While many…

Video frame interpolation aims at synthesizing intermediate frames from nearby source frames while maintaining spatial and temporal consistencies. The existing deep-learning-based video frame interpolation methods can be roughly divided…

Computer Vision and Pattern Recognition · Computer Science 2021-03-19 Zhihao Shi , Xiaohong Liu , Kangdi Shi , Linhui Dai , Jun Chen

Let $A$ be a square complex matrix, $z_1$, ..., $z_{n}\in\mathbb C$ be (possibly repetitive) points of interpolation, $f$ be analytic in a neighborhood of the convex hull of the union of the spectrum of $A$ and the points $z_1$, ...,…

Numerical Analysis · Mathematics 2019-02-19 V. G. Kurbatov , I. V. Kurbatova

In this paper, we study arbitrary order extended finite element (XFE) methods based on two discontinuous Galerkin (DG) schemes in order to solve elliptic interface problems in two and three dimensions. Optimal error estimates in the…

Numerical Analysis · Mathematics 2016-04-22 Fei Wang , Yuanming Xiao , Jinchao Xu

In this paper we use the GeneralizedMultiscale Finite ElementMethod (GMsFEM) framework, introduced in [20], in order to solve nonlinear elliptic equations with high-contrast coefficients. The proposed solution method involves linearizing…

Analysis of PDEs · Mathematics 2016-08-24 Yalchin Efendiev , Juan Galvis , Guanglian Li , Michael Presho

We study a mixed-integer set $S:=\{(x,t) \in \{0,1\}^n \times \mathbb{R}: f(x) \ge t\}$ arising in the submodular maximization problem, where $f$ is a submodular function defined over $\{0,1\}^n$. We use intersection cuts to tighten a…

Optimization and Control · Mathematics 2023-02-28 Liding Xu , Leo Liberti

In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite…

Numerical Analysis · Mathematics 2015-06-12 Yalchin Efendiev , Juan Galvis , Thomas Y. Hou

Using the standard finite element method (FEM) to solve general partial differential equations, the round-off error is found to be proportional to $N^{\beta_{\rm R}}$, with $N$ the number of degrees of freedom (DoFs) and $\beta_{\rm R}$ a…

Numerical Analysis · Mathematics 2022-02-08 Jie Liu , Henk M. Schuttelaars , Matthias Möller