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By using the Hadamard matrix product concept, this paper introduces two generalized matrix formulation forms of numerical analogue of nonlinear differential operators. The SJT matrix-vector product approach is found to be a simple,…

Computational Engineering, Finance, and Science · Computer Science 2024-09-21 W. Chen

Taylor's formula holds significant importance in function representation, such as solving differential difference equations, ordinary differential equations, partial differential equations, and further promotes applications in visual…

Machine Learning · Computer Science 2025-07-15 Guoyou Wang , Yihua Tan , Shiqi Liu

Deep neural networks (DNNs) have achieved remarkable empirical success, yet the absence of a principled theoretical foundation continues to hinder their systematic development. In this survey, we present differential equations as a…

Artificial Intelligence · Computer Science 2026-03-20 Hongjue Zhao , Yizhuo Chen , Yuchen Wang , Hairong Qi , Lui Sha , Tarek Abdelzaher , Huajie Shao

Differential reformulations of field theories are often used for explicit computations. We derive a one-matrix differential formulation of two-matrix models, with the help of which it is possible to diagonalize the one- and two-matrix…

Mathematical Physics · Physics 2022-10-05 Joren Brunekreef , Luca Lionni , Johannes Thürigen

In this paper, we study numerical methods for the homogenization of linear second-order elliptic equations in nondivergence-form with periodic diffusion coefficients and large drift terms. Upon noting that the effective diffusion matrix can…

Numerical Analysis · Mathematics 2025-06-18 Timo Sprekeler , Han Wu , Zhiwen Zhang

We describe the extension, beyond fundamental representations of the Yang-Baxter algebra, of our new construction of separation of variables bases for quantum integrable lattice models. The key idea underlying our approach is to use the…

Mathematical Physics · Physics 2021-02-10 J. M. Maillet , G. Niccoli

We reexamine the recently introduced basis-set correction theory based on density-functional theory consisting in correcting the basis-set incompleteness error of wave-function methods using a density functional. We use a one-dimensional…

Chemical Physics · Physics 2022-02-16 Diata Traore , Emmanuel Giner , Julien Toulouse

We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components. An RBF component is a generalization of the outer product between a pair of vectors, where an RBF function replaces the…

Machine Learning · Computer Science 2021-06-25 Elizaveta Rebrova , Yu-Hang Tang

It is known that the unified transform method may be used to solve any well-posed initial-boundary value problem for a linear constant-coefficient evolution equation on the finite interval or the half-line. In contrast, classical methods…

Spectral Theory · Mathematics 2014-08-19 David A. Smith

In this paper we develop a discrete Hierarchical Basis (HB) to efficiently solve the Radial Basis Function (RBF) interpolation problem with variable polynomial order. The HB forms an orthogonal set and is adapted to the kernel seed function…

Numerical Analysis · Computer Science 2023-11-21 Julio Enrique Castrillon-Candas , Jun Li , Victor Eijkhout

We present a quantum algorithm for systems of (possibly inhomogeneous) linear ordinary differential equations with constant coefficients. The algorithm produces a quantum state that is proportional to the solution at a desired final time.…

Quantum Physics · Physics 2017-11-07 Dominic W. Berry , Andrew M. Childs , Aaron Ostrander , Guoming Wang

In this paper we propose spectral tools based on non-decimated complex wavelet transforms implemented by their matrix formulation. This non-decimated complex wavelet spectra utilizes both real and imaginary parts of complex-valued wavelet…

Applications · Statistics 2019-02-05 Taewoon Kong , Brani Vidakovic

In this work, we introduce the new class of functions which can use to solve the nonlinear/linear multi-dimensional differential equations. Based on these functions, a numerical method is provided which is called the Developed Lagrange…

Numerical Analysis · Mathematics 2019-04-30 Mehdi Delkhosh , Kourosh Parand , Amir H. Hadian-Rasanan

Partial differential equations can be used to model many problems in several fields of application including, e.g., fluid mechanics, heat and mass transfer, and electromagnetism. Accurate discretization methods (e.g., finite element or…

Numerical Analysis · Mathematics 2022-03-18 Pierfrancesco Siena , Michele Girfoglio , Gianluigi Rozza

The fast multipole method (FMM) has had great success in reducing the computational complexity of solving the boundary integral form of the Helmholtz equation. We present a formulation of the Helmholtz FMM that uses Fourier basis functions…

Numerical Analysis · Mathematics 2014-03-20 Cris Cecka , Eric Darve

We present a new technique for constructing solutions of quasilinear systems of first-order partial differential equations, in particular inhomogeneous ones. A generalization of the Riemann invariants method to the case of inhomogeneous…

Mathematical Physics · Physics 2014-10-01 Alfred Michel Grundland , Vincent Lamothe

In this paper, we propose a Two-Step Linear Mixing Model (2LMM) that bridges the gap between model complexity and computational tractability. The model achieves this by introducing two distinct scaling steps: an endmember scaling step…

Image and Video Processing · Electrical Eng. & Systems 2025-12-04 Xander Haijen , Bikram Koirala , Xuanwen Tao , Paul Scheunders

In this article, we describe an approach for solving partial differential equations with general boundary conditions imposed on arbitrarily shaped boundaries. A function that has a prescribed value on the domain in which a differential…

Mathematical Physics · Physics 2009-12-08 Hui-Chia Yu , Hsun-Yi Chen , K. Thornton

Recently we showed how non-homogeneous second-order difference equations appearing within ABJM quantum spectral curve description could be solved using Mellin space technique. In particular we provided explicit results for anomalous…

High Energy Physics - Theory · Physics 2019-05-01 R. N. Lee , A. I. Onishchenko

The coincidence between polynomial neural networks and matrix Lie maps is discussed in the article. The matrix form of Lie transform is an approximation of the general solution of the nonlinear system of ordinary differential equations. It…

Neural and Evolutionary Computing · Computer Science 2019-08-20 Andrei Ivanov , Sergei Andrianov
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