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Two-level domain decomposition preconditioners lead to fast convergence and scalability of iterative solvers. However, for highly heterogeneous problems, where the coefficient function is varying rapidly on several possibly non-separated…

Numerical Analysis · Mathematics 2022-07-13 Alexander Heinlein , Kathrin Smetana

We introduce a numerical method for the approximation of functions which are analytic on compact intervals, except at the endpoints. This method is based on variable transforms using particular parametrized exponential and…

Numerical Analysis · Mathematics 2016-09-06 Ben Adcock , Jésus Martín-Vaquero , Mark Richardson

This paper uses the Modified Projection Method to examine the errors in solving the boundary integral equation from Laplace equation. The analysis uses weighted norms, and parallel algorithms help solve the independent linear systems. By…

Numerical Analysis · Mathematics 2024-11-04 Akshay Rane , Kunalkumar Shelar

We present an adaptive regularization scheme for optimizing composite energy functionals arising in image analysis problems. The scheme automatically trades off data fidelity and regularization depending on the current data fit during the…

Computer Vision and Pattern Recognition · Computer Science 2017-05-10 Byung-Woo Hong , Ja-Keoung Koo , Martin Burger , Stefano Soatto

Classical neural ordinary differential equations (ODEs) are powerful tools for approximating the log-density functions in high-dimensional spaces along trajectories, where neural networks parameterize the velocity fields. This paper…

Optimization and Control · Mathematics 2025-01-30 Mo Zhou , Stanley Osher , Wuchen Li

We propose a finite-dimensional control-based method to approximate solution operators for evolutional partial differential equations (PDEs), particularly in high-dimensions. By employing a general reduced-order model, such as a deep neural…

Numerical Analysis · Mathematics 2024-01-22 Nathan Gaby , Xiaojing Ye

This paper proposes two efficient approximation methods to solve high-dimensional fully nonlinear partial differential equations (NPDEs) and second-order backward stochastic differential equations (2BSDEs), where such high-dimensional fully…

Numerical Analysis · Mathematics 2023-01-18 Xu Xiao , Wenlin Qiu , Omid Nikan

We give a review of the exact renormalization group (ERG) approach and illustrate its applications in scalar and fermionic theories. The derivative expansion and approximations based on the derivative expansion with further truncation in…

High Energy Physics - Theory · Physics 2008-02-03 Jordi Comellas , Yuri Kubyshin , Enrique Moreno

Ordinary differential equations (ODEs) are widely used to characterize the dynamics of complex systems in real applications. In this article, we propose a novel joint estimation approach for generalized sparse additive ODEs where…

Methodology · Statistics 2022-08-19 Nan Zhang , Muye Nanshan , Jiguo Cao

We present a novel approach that redefines the traditional interpretation of explicit and implicit discretization methods for solving a general class of advection-diffusion equations (ADEs) featuring nonlinear advection, diffusion…

Analysis of PDEs · Mathematics 2025-06-10 Amin Jafarimoghaddam , Manuel Soler , Irene Ortiz

Strong approximation errors of both finite element semi-discretization and spatio-temporal full discretization are analyzed for the stochastic Allen-Cahn equation driven by additive noise in space dimension $d \leq 3$. The full…

Numerical Analysis · Mathematics 2020-08-04 Ruisheng Qi , Xiaojie Wang

We study exact renormalisation group equations for the 3d Ising universality class. At the Wilson-Fisher fixed point, symmetric and antisymmetric correction-to-scaling exponents are computed with high accuracy for an optimised cutoff to…

High Energy Physics - Theory · Physics 2009-11-10 Daniel F. Litim , Lautaro Vergara

It is well known that exact notions of model abstraction and reduction for dynamical systems may not be robust enough in practice because they are highly sensitive to the specific choice of parameters. In this paper we consider this problem…

Systems and Control · Computer Science 2018-07-19 Luca Cardelli , Mirco Tribastone , Max Tschaikowski , Andrea Vandin

A numerical method for solving elliptic PDEs with variable coefficients on two-dimensional domains is presented. The method is based on high-order composite spectral approximations and is designed for problems with smooth solutions. The…

Numerical Analysis · Mathematics 2013-07-11 A. Gillman , P. G. Martinsson

This paper considers the approximation of partial differential equations with a point collocation framework based on high-order local maximum-entropy schemes (HOLMES). In this approach, smooth basis functions are computed through an…

Computational Engineering, Finance, and Science · Computer Science 2020-11-02 F. Greco , M. Arroyo

We analyze the problem of global reconstruction of functions as accurately as possible, based on partial information in the form of a truncated power series at some point, and additional analyticity properties. This situation occurs…

Complex Variables · Mathematics 2022-05-30 Ovidiu Costin , Gerald V. Dunne

In this article, we propose a new numerical approach to high-dimensional partial differential equations (PDEs) arising in the valuation of exotic derivative securities. The proposed method is extended from Reisinger and Wittum (2007) and…

Computational Finance · Quantitative Finance 2013-10-04 Christoph Reisinger , Rasmus Wissmann

The method of boundary curve reparametrization is applied to construction of the approximate analytical conformal mapping of the unit disk onto an arbitrary given finite domain with a boundary smooth at every point but fininte number of…

Complex Variables · Mathematics 2023-07-10 Pyotr N. Ivanshin , Elena A. Shirokova

We propose a method for the treatment of two--point boundary value problems given by nonlinear ordinary differential equations. The approach leads to sequences of roots of Hankel determinants that converge rapidly towards the unknown…

Mathematical Physics · Physics 2007-05-29 Paolo Amore , Francisco M. Fernandez

We present effective numerical algorithms for locally recovering unknown governing differential equations from measurement data. We employ a set of standard basis functions, e.g., polynomials, to approximate the governing equation with high…

Numerical Analysis · Mathematics 2020-05-05 Kailiang Wu , Dongbin Xiu