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In this work we propose a novel approach to investigate boundary value problems (BVPs) for fully third order differential equations. It is based on the reduction of BVPs to operator equations for the nonlinear terms but not for the…

Numerical Analysis · Mathematics 2018-06-04 Dang Quang A , Dang Quang Long

In this paper we propose an adaptive scheme for the solution of time-dependent boundary value problems (BVPs). To solve numerically these problems, we consider the kernel-based method of lines that allows us to split the spatial and time…

Numerical Analysis · Mathematics 2022-03-29 Roberto Cavoretto

A new technique is presented to solve a class of linear boundary value problems (BVP). Technique is primarily based on an operational matrix developed from a set of modified Bernoulli polynomials. The new set of polynomials is an…

Computational Engineering, Finance, and Science · Computer Science 2020-08-14 Udaya Pratap Singh

Working with systems of partial differential equations (PDEs) is a fundamental task in computational science. Well-posed systems are addressed by numerical solvers or neural operators, whereas systems described by data are often addressed…

Machine Learning · Statistics 2025-09-30 Jianlei Huang , Marc Härkönen , Markus Lange-Hegermann , Bogdan Raiţă

In this work we present a method, based on the use of Bernstein polynomials, for the numerical resolution of some boundary values problems. The computations have not need of particular approximations of derivatives, such as finite…

Numerical Analysis · Mathematics 2025-10-20 Gianluca Argentini

In this paper we construct optimal, in certain sense, estimates of values of linear functionals on solutions to two-point boundary value problems (BVPs) for systems of linear first-order ordinary differential equations from observations…

Classical Analysis and ODEs · Mathematics 2009-12-16 Olexandr Nakonechnyi , Yury Podlipenko , Yury Shestopalov

This paper is devoted to find the numerical solutions of one dimensional general nonlinear system of third-order boundary value problems (BVPs) for the pair of functions using Galerkin weighted residual method. We derive mathematical…

Numerical Analysis · Mathematics 2024-04-24 Snigdha Dhar , Md. Shafiqul Islam

We consider finite-horizon Markov Decision Processes where parameters, such as transition probabilities, are unknown and estimated from data. The popular distributionally robust approach to addressing the parameter uncertainty can sometimes…

Systems and Control · Electrical Eng. & Systems 2022-10-07 Yifan Lin , Yuxuan Ren , Enlu Zhou

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

We develop methods for the solution of inhomogeneous Robin type boundary value problems (BVPs) that arise for certain linear parabolic Partial Differential Equations (PDEs) on a half line, as well as a second order generalisation. We are…

Analysis of PDEs · Mathematics 2023-11-22 Mark Craddock , Martino Grasselli , Andrea Mazzoran

In this paper, we present a new iterative approximate method of solving boundary value problems. The idea is to compute approximate polynomial solutions in the Bernstein form using least squares approximation combined with some properties…

Numerical Analysis · Computer Science 2017-09-08 Przemysław Gospodarczyk , Paweł Woźny

In this paper, we consider a boundary value problem (BVP) for a fourth order nonlinear functional integro-differential equation. We establish the existence and uniqueness of solution and construct a numerical method for solving it. We prove…

Numerical Analysis · Mathematics 2021-11-29 Dang Quang A , Pham Huy Dien , Dang Quang Long

A Neural Network (NN) based numerical method is formulated and implemented for solving Boundary Value Problems (BVPs) and numerical results are presented to validate this method by solving Laplace equation with Dirichlet boundary condition…

Machine Learning · Computer Science 2019-09-25 Sethu Hareesh Kolluru

Linear second order elliptic boundary value problems (BVP) on bounded Lipschitz domains are studied in the case of Gaussian white noise loads. Especially, Neumann and Robin BVPs are considered. The main obstacle for applying the usual…

Probability · Mathematics 2016-03-03 Sari Lasanen , Lassi Roininen , Janne M. J. Huttunen

Inverse problems involving partial differential equations (PDEs) are widely used in science and engineering. Although such problems are generally ill-posed, different regularisation approaches have been developed to ameliorate this problem.…

Applications · Statistics 2022-03-23 Jan Povala , Ieva Kazlauskaite , Eky Febrianto , Fehmi Cirak , Mark Girolami

We propose a novel approach which employs random sampling to generate an accurate non-uniform mesh for numerically solving Partial Differential Equation Boundary Value Problems (PDE-BVP's). From a uniform probability distribution U over a…

Numerical Analysis · Mathematics 2011-03-29 David Bortz , Andrew Christlieb

A new approach for solving stiff boundary value problems for systems of ordinary differential equations is presented. Its idea essentially generalizes and extends that from arXiv:1601.04272v8. The approach can be viewed as a methodology…

Numerical Analysis · Mathematics 2021-11-30 Denys Dragunov

We derive explicit solution representations for linear, dissipative, second-order Initial-Boundary Value Problems (IBVPs) with coefficients that are spatially varying, with linear, constant-coefficient, two-point boundary conditions. We…

Analysis of PDEs · Mathematics 2024-06-04 Matthew Farkas , Bernard Deconinck

We derive new boundary conditions and implementation procedures for nonlinear initial boundary value problems (IBVPs) with non-zero boundary data that lead to bounded solutions. The new boundary procedure is applied to nonlinear IBVPs in…

Numerical Analysis · Mathematics 2024-12-31 Jan Nordström

Bayesian optimisation requires fitting a Gaussian process model, which in turn requires specifying prior on the unknown black-box function -- most of the theoretical literature assumes this prior is known. However, it is common to have more…

Machine Learning · Computer Science 2025-02-25 Juliusz Ziomek , Masaki Adachi , Michael A. Osborne
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