English
Related papers

Related papers: Meshless Hermite-HDMR finite difference method for…

200 papers

High-dimensional complex multi-parameter problems are prevalent in engineering, exceeding the capabilities of traditional surrogate models designed for low/medium-dimensional problems. These models face the curse of dimensionality,…

Methodology · Statistics 2023-07-06 Yili Zhang , Hanyan Huang , Mei Xiong , Zengquan Yao

Based on the ideas of arXiv:1710.06612, we consider the problem of minimization of the Holder-continuous non-smooth functional $f$ with non-positive convex (generally, non-smooth) Lipschitz-continuous functional constraint. We propose some…

Optimization and Control · Mathematics 2022-01-03 Fedor Stonyakin , Alexey Stepanov , Alexander Gasnikov , Alexander Titov

Due to properties such as interpolation, smoothness, and spline connections, Hermite subdivision schemes employ fast iterative algorithms for geometrically modeling curves/surfaces in CAGD and for building Hermite wavelets in numerical…

Numerical Analysis · Mathematics 2024-08-12 Bin Han

We propose a multiscale approach for an elliptic multiscale setting with general unstructured diffusion coefficients that is able to achieve high-order convergence rates with respect to the mesh parameter and the polynomial degree. The…

Numerical Analysis · Mathematics 2020-09-03 Roland Maier

Since the advent of mesh-free methods as a tool for the numerical analysis of systems of Partial Differential Equations (PDEs), many variants of differential operator approximation have been proposed. In this work, we propose a local…

Numerical Analysis · Mathematics 2022-03-07 Mitja Jančič , Gregor Kosec

In this paper we consider the numerical solution of the Hamiltonian wave equation in two spatial dimension. We use the Mimetic Finite Difference (MFD) method to approximate the continuous problem combined with a symplectic integration in…

Numerical Analysis · Mathematics 2016-08-04 Lourenco Beirao da Veiga , Luciano Lopez , Giuseppe Vacca

We introduce a diffuse interface box method (DIBM) for the numerical approximation on complex geometries of elliptic problems with Dirichlet boundary conditions. We derive a priori $H^1$ and $L^2$ error estimates highlighting the r\^{o}le…

Numerical Analysis · Mathematics 2021-04-27 G. Negrini , N. Parolini , M. Verani

In this paper, we introduce a new method for solving variational inequality problems with monotone and Lipschitz-continuous mapping in Hilbert space. The iterative process is based on two well-known projection method and the hybrid (or…

Optimization and Control · Mathematics 2015-01-30 Yu. V. Malitsky , V. V. Semenov

We propose a new first-order optimisation algorithm to solve high-dimensional non-smooth composite minimisation problems. Typical examples of such problems have an objective that decomposes into a non-smooth empirical risk part and a…

Optimization and Control · Mathematics 2015-07-07 Niao He , Zaid Harchaoui

In this paper, we develop sixth-order hybrid finite difference methods (FDMs) for the elliptic interface problem $-\nabla \cdot( a\nabla u)=f$ in $\Omega\backslash \Gamma$, where $\Gamma$ is a smooth interface inside $\Omega$. The variable…

Numerical Analysis · Mathematics 2023-11-13 Qiwei Feng , Bin Han , Peter Minev

In this paper we develop finite difference schemes for elliptic problems with piecewise continuous coefficients that have (possibly huge) jumps across fixed internal interfaces. In contrast with such problems involving one smooth…

Numerical Analysis · Mathematics 2023-02-21 Qiwei Feng , Bin Han , Peter Minev

Computational analysis with the finite element method requires geometrically accurate meshes. It is well known that high-order meshes can accurately capture curved surfaces with fewer degrees of freedom in comparison to low-order meshes.…

Mathematical Software · Computer Science 2024-01-30 Ketan Mittal , Veselin A. Dobrev , Patrick Knupp , Tzanio Kolev , Franck Ledoux , Claire Roche , Vladimir Z. Tomov

Distance metric learning (DML) approaches learn a transformation to a representation space where distance is in correspondence with a predefined notion of similarity. While such models offer a number of compelling benefits, it has been…

Machine Learning · Statistics 2016-03-03 Oren Rippel , Manohar Paluri , Piotr Dollar , Lubomir Bourdev

Differentiable rendering is a technique that aims to invert the rendering process to enable optimizing rendering parameters from a set of images. In this article, we present a differentiable volume rendering solution called DiffTetVR for…

Graphics · Computer Science 2026-01-05 Christoph Neuhauser

We propose a general algorithm for non-conforming adaptive mesh refinement (AMR) of unstructured meshes in high-order finite element codes. Our focus is on h-refinement with a fixed polynomial order. The algorithm handles triangular,…

Numerical Analysis · Computer Science 2019-05-13 Jakub Červený , Veselin Dobrev , Tzanio Kolev

Deep learning and the collocation method are merged and used to solve partial differential equations describing structures' deformation. We have considered different types of materials: linear elasticity, hyperelasticity (neo-Hookean) with…

Machine Learning · Computer Science 2021-11-24 Diab W. Abueidda , Qiyue Lu , Seid Koric

This paper presents an efficient parallel direct algorithm with near-optimal complexity for the compact fourth and sixth-order approximation of the three-dimensional Helmholtz equations [1] with the problem coefficient depending on only one…

Numerical Analysis · Mathematics 2020-03-13 Ronald Gonzales , Yury Gryazin , Yun Teck Lee

A number of basic image processing tasks, such as any geometric transformation require interpolation at subpixel image values. In this work we utilize the multidimensional coordinate Hermite spline interpolation defined on non-equal spaced,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Konstantinos K. Delibasis , Iro Oikonomou , Aristides I. Kechriniotis , Georgios N. Tsigaridas

The idea of using fragment embedding to circumvent the high computational scaling of accurate electronic structure methods while retaining high accuracy has been a long-standing goal for quantum chemists. Traditional fragment embedding…

Chemical Physics · Physics 2022-10-11 Hong-Zhou Ye , Matthew Welborn , Nathan D. Ricke , Troy Van Voorhis

Using deep neural networks to solve PDEs has attracted a lot of attentions recently. However, why the deep learning method works is falling far behind its empirical success. In this paper, we provide a rigorous numerical analysis on deep…

Numerical Analysis · Mathematics 2021-09-07 Yuling Jiao , Yanming Lai , Yisu Lo , Yang Wang , Yunfei Yang
‹ Prev 1 8 9 10 Next ›