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In the past decades, the finite difference methods for space fractional operators develop rapidly; to the best of our knowledge, all the existing finite difference schemes, including the first and high order ones, just work on uniform…

Numerical Analysis · Mathematics 2016-04-04 Lijing Zhao , Weihua Deng

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian…

Machine Learning · Statistics 2014-02-13 Philipp Hennig , Søren Hauberg

Given a first-order autonomous algebraic ordinary differential equation, we present a method for computing formal power series solutions by means of places. We provide an algorithm for computing a full characterization of possible initial…

Symbolic Computation · Computer Science 2018-11-15 Sebastian Falkensteiner , J. Rafael Sendra

A step-search sequential quadratic programming method is proposed for solving nonlinear equality constrained stochastic optimization problems. It is assumed that constraint function values and derivatives are available, but only stochastic…

Optimization and Control · Mathematics 2024-10-08 Albert S. Berahas , Miaolan Xie , Baoyu Zhou

Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this work, we explain the mathematical assumptions and detailed…

Machine Learning · Statistics 2021-10-25 Nicholas Krämer , Nathanael Bosch , Jonathan Schmidt , Philipp Hennig

We address a new numerical scheme based on a class of machine learning methods, the so-called Extreme Learning Machines with both sigmoidal and radial-basis functions, for the computation of steady-state solutions and the construction of…

Numerical Analysis · Mathematics 2023-03-17 Gianluca Fabiani , Francesco Calabrò , Lucia Russo , Constantinos Siettos

This article examines a new approach to solving ordinary differential equations based on Fractional-Calculus theory. Poisson and Sturm-Liouville-type problems are studied, together with different boundary conditions. Each case is analyzed…

Numerical Analysis · Mathematics 2023-05-29 Sergio F. Yapur

A class of quasilinear singularly perturbed boundary value problems with a turning point of attractive type is considered. The problems are solved numerically by a finite-difference scheme on a special discretization mesh which is dense…

Numerical Analysis · Mathematics 2015-04-21 Relja Vulanović

A new method for finding first integrals of discrete equations is presented. It can be used for discrete equations which do not possess a variational (Lagrangian or Hamiltonian) formulation. The method is based on a newly established…

Exactly Solvable and Integrable Systems · Physics 2013-11-08 V. Dorodnitsyn , E. Kaptsov , R. Kozlov , P. Winternitz

In this work, we develop a localized numerical scheme with low regularity requirements for solving time-fractional integro-differential equations. First, a fully discrete numerical scheme is constructed. Specifically, for temporal…

Numerical Analysis · Mathematics 2025-12-02 Lijing Zhao , Rui Zhao , Wenyi Tian , Yufeng Nie

The porous medium equation (PME) is a typical nonlinear degenerate parabolic equation. An energetic variational approach has been studied in a recent work [6], in which the trajectory equation is obtained, and a few first order accurate…

Numerical Analysis · Mathematics 2020-06-23 Chenghua Duan , Wenbin Chen , Chun Liu , Cheng Wang , Xingye Yue

We provide of a method to integrate first order non-linear systems of differential equations with variable coefficients. It determines approximate solutions given initial or boundary conditions or even for Sturm-Liouville problems. This…

Classical Analysis and ODEs · Mathematics 2025-03-05 Manuel Gadella , Luis P. Lara

Given a stochastic differential equation (SDE) in $\mathbb{R}^n$ whose solution is constrained to lie in some manifold $M \subset \mathbb{R}^n$, we propose a class of numerical schemes for the SDE whose iterates remain close to $M$ to high…

Numerical Analysis · Mathematics 2020-09-24 John Armstrong , Tim King

This paper introduces specular differentiation, which generalizes G\^ateaux and Fr\'echet differentiation in normed vector spaces. We investigate its fundamental theoretical properties and establish weak forms of the Mean Value Theorem and…

Optimization and Control · Mathematics 2026-05-27 Kiyuob Jung

We show a novel systematic way to construct conservative finite difference schemes for quasilinear first-order system of ordinary differential equations with conserved quantities. In particular, this includes both autonomous and…

Numerical Analysis · Mathematics 2018-05-23 Andy T. S. Wan , Alexander Bihlo , Jean-Christophe Nave

In this study, we propose high-order implicit and semi-implicit schemes for solving ordinary differential equations (ODEs) based on Taylor series expansion. These methods are designed to handle stiff and non-stiff components within a…

Numerical Analysis · Mathematics 2024-09-19 S. Boscarino , E. Macca

Several neural network approaches for solving differential equations employ trial solutions with a feedforward neural network. There are different means to incorporate the trial solution in the construction, for instance one may include…

Neural and Evolutionary Computing · Computer Science 2021-12-01 Toni Schneidereit , Michael Breuß

Over the past few decades, there has been substantial interest in evolution equations that involving a fractional-order derivative of order $\alpha\in(0,1)$ in time, due to their many successful applications in engineering, physics, biology…

Numerical Analysis · Mathematics 2019-01-30 Bangti Jin , Raytcho Lazarov , Zhi Zhou

In this paper we are considering a semilinear singular perturbation reaction -- diffusion boundary value problem, which contains a small perturbation parameter that acts on the highest order derivative. We construct a difference scheme on…

Numerical Analysis · Mathematics 2015-09-25 Enes Duvnjaković , Samir Karasuljić , Vedad Pasic , Helena Zarin

We consider initial value problems of nonlinear dynamical systems, which include physical parameters. A quantity of interest depending on the solution is observed. A discretisation yields the trajectories of the quantity of interest in many…

Machine Learning · Computer Science 2021-01-13 Roland Pulch , Maha Youssef
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