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In recent years, a variety of meshless methods have been developed to solve partial differential equations in complex domains. Meshless methods discretize the partial differential equations over scattered points instead of grids. Radial…

Numerical Analysis · Mathematics 2021-06-17 Naman Bartwal , Shantanu Shahane , Somnath Roy , Surya Pratap Vanka

We discuss exact analytical solutions of a variety of statistical models recently obtained for finite systems by a novel powerful mathematical method, the Laplace-Fourier transform. Among them are a constrained version of the statistical…

Nuclear Theory · Physics 2008-11-26 K. A. Bugaev

We report on the possibilities of using the method of normal fundamental systems for solving some problems of oscillation theory. Large elastic dynamical systems with continuous and discrete parameters are considered, which have many…

Numerical Analysis · Mathematics 2007-05-23 Olena V. Mul , Delfim F. M. Torres

We present the general forms of piece-wise functions on partitioned domains satisfying an intrinsic $C^0$ or $C^1$ continuity across the sub-domain boundaries. These general forms are constructed based on a strategy stemming from the theory…

Numerical Analysis · Mathematics 2024-03-12 Jielin Yang , Suchuan Dong

The problem of increasing the accuracy of an approximate solution is considered for boundary value problems for parabolic equations. For ordinary differential equations (ODEs), nonstandard finite difference schemes are in common use for…

Numerical Analysis · Computer Science 2017-05-22 Petr N. Vabishchevich

Exceptionally elegant formulae exist for the fractional Laplacian operator applied to weighted classical orthogonal polynomials. We utilize these results to construct a solver, based on frame properties, for equations involving the…

Numerical Analysis · Mathematics 2025-07-24 Ioannis P. A. Papadopoulos , Timon S. Gutleb , José A. Carrillo , Sheehan Olver

Sparse matrix factorization is a popular tool to obtain interpretable data decompositions, which are also effective to perform data completion or denoising. Its applicability to large datasets has been addressed with online and randomized…

Machine Learning · Statistics 2017-11-15 Arthur Mensch , Julien Mairal , Bertrand Thirion , Gaël Varoquaux

A conformal flattening maps a curved surface to the plane without distorting angles---such maps have become a fundamental building block for problems in geometry processing, numerical simulation, and computational design. Yet existing…

Graphics · Computer Science 2018-01-30 Rohan Sawhney , Keenan Crane

This paper introduces a fast and numerically stable algorithm for the solution of fourth-order linear boundary value problems on an interval. This type of equation arises in a variety of settings in physics and signal processing. Our method…

Numerical Analysis · Computer Science 2020-01-13 William Leeb , Vladimir Rokhlin

Solving partial differential equations (PDEs) with highly oscillatory solutions on complex domains remains a challenging and important problem. High-frequency oscillations and intricate geometries often result in prohibitively expensive…

Numerical Analysis · Mathematics 2025-10-28 Gareth Hardwick , Haizhao Yang

Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales (see Figure 1 for the illustration of a perforated domain).…

Numerical Analysis · Mathematics 2015-01-16 Eric T. Chung , Yalchin Efendiev , Guanglian Li , Maria Vasilyeva

Periodic micromagnetic finite element method (PM-FEM) is introduced to solve periodic unit cell problems using the Landau-Lifshitz-Gilbert equation. PM-FEM is applicable to general problems with 1D, 2D, and 3D periodicities. PM-FEM is based…

Numerical Analysis · Mathematics 2024-09-24 Fangzhou Ai , Jiawei Duan , Vitaliy Lomakin

In this paper, we study a class of nonsmooth fractional programs {\rm (FP, for short)} with SOS-convex semi-algebraic functions. Under suitable assumptions, we derive a strong duality result between the problem (FP) and its semidefinite…

Optimization and Control · Mathematics 2024-01-31 Chengmiao Yang , Liguo Jiao , Jae Hyoung Lee

Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been applied in several applications, it does not always result in…

Machine Learning · Computer Science 2007-05-23 Patrik O. Hoyer

This paper presents a novel mass-conservative mixed multiscale method for solving flow equations in heterogeneous porous media. The media properties (the permeability) contain multiple scales and high contrast. The proposed method solves…

Numerical Analysis · Mathematics 2019-04-01 Eric Chung , Yalchin Efendiev , Wing Tat Leung

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over…

Machine Learning · Computer Science 2017-11-15 Shing Chan , Ahmed H. Elsheikh

An efficient numerical method is proposed for computing the Dirichlet-to-Neumann (DtN) map associated with the exterior Dirichlet problem for the two-dimensional Helmholtz equation with an inhomogeneous term. The exterior solution is…

Numerical Analysis · Mathematics 2026-03-17 Takemi Shigeta

We focus on the initial boundary value problem for a general scalar balance law in one space dimension. Under rather general assumptions on the flux and source functions, we prove the well-posedness of this problem and the stability of its…

Analysis of PDEs · Mathematics 2018-09-18 Elena Rossi

Factorization machine (FM) variants are widely used for large scale real-time content recommendation systems, since they offer an excellent balance between model accuracy and low computational costs for training and inference. These systems…

Machine Learning · Computer Science 2025-01-03 Alex Shtoff , Elie Abboud , Rotem Stram , Oren Somekh

Many modern datasets, from areas such as neuroimaging and geostatistics, come in the form of a random sample of tensor-valued data which can be understood as noisy observations of a smooth multidimensional random function. Most of the…

Methodology · Statistics 2023-09-18 William Consagra , Arun Venkataraman , Xing Qiu