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We derive computable upper bounds for the difference between an exact solution of the evolutionary convection-diffusion problem and an approximation of this solution. The estimates are obtained by certain transformations of the integral…

Numerical Analysis · Mathematics 2013-12-02 Sergey I. Repin , Satyendra K. Tomar

We study finite element approximations of second-order elliptic problems with measure-valued right-hand sides supported on lower-dimensional sets. The exact solution generally lacks $H^1$-regularity due to the source singularity, which…

Numerical Analysis · Mathematics 2026-03-10 Huadong Gao , Yuhui Huang

We propose a new and simpler residual based a posteriori error estimator for finite element approximation of the elliptic obstacle problem. The results in the article are two fold. Firstly, we address the influence of the inhomogeneous…

Numerical Analysis · Mathematics 2016-11-10 Sharat Gaddam , Thirupathi Gudi

Probabilistic numerical solvers for ordinary differential equations (ODEs) treat the numerical simulation of dynamical systems as problems of Bayesian state estimation. Aside from producing posterior distributions over ODE solutions and…

Numerical Analysis · Mathematics 2024-09-12 Nathanael Bosch , Adrien Corenflos , Fatemeh Yaghoobi , Filip Tronarp , Philipp Hennig , Simo Särkkä

The solutions of fractional differential equations (FDEs) have a natural singularity at the initial point. The accuracy of their numerical solutions is lower than the accuracy of the numerical solutions of FDEs whose solutions are…

Numerical Analysis · Mathematics 2018-06-11 Yuri Dimitrov , Ivan Dimov , Venelin Todorov

Numerical solutions of differential equations are usually not smooth functions. However, they should resemble the smoothness of the corresponding real solutions in one way or another. In two of our recent papers, a kind of spacial…

Numerical Analysis · Mathematics 2012-07-13 Tong Sun

Ordinary differential equation (ODE) models are widely used to describe systems in many areas of science. To ensure these models provide accurate and interpretable representations of real-world dynamics, it is often necessary to infer…

Methodology · Statistics 2026-03-24 Selva Salimi , David J. Warne , Christopher Drovandi

We derive efficient and reliable goal-oriented error estimations, and devise adaptive mesh procedures for the finite element method that are based on the localization of a posteriori estimates. In our previous work [SIAM J. Sci. Comput.,…

Numerical Analysis · Mathematics 2020-03-23 Bernhard Endtmayer , Ulrich Langer , Thomas Wick

We aim to identify the generating, ordinary differential equation (ODE) from a set of trajectories of a partially observed system. Our approach does not need prescribed basis functions to learn the ODE model, but only a rich set of Neural…

Machine Learning · Statistics 2020-03-13 Niklas Heim , Václav Šmídl , Tomáš Pevný

In this paper, the a posteriori error estimates of the exponential midpoint method for time discretization are studied for linear and semilinear parabolic equations. Using the exponential midpoint approximation defined by a continuous and…

Numerical Analysis · Mathematics 2024-06-13 Xianfa Hu , Wansheng Wang , Mengli Mao , Jiliang Cao

This paper is concerned with the derivation of computable and guaranteed upper bounds of the difference between the exact and the approximate solution of an exterior domain boundary value problem for a linear elliptic equation. Our analysis…

Analysis of PDEs · Mathematics 2011-05-23 Dirk Pauly , Sergey Repin

Optimal convergence rates of adaptive finite element methods are well understood in terms of the axioms of adaptivity. One key ingredient is the discrete reliability of a residual-based a posteriori error estimator, which controls the error…

Numerical Analysis · Mathematics 2019-11-06 Carsten Carstensen , Sophie Puttkammer

Ordinary Differential Equations (ODEs) are widely used in physics, chemistry, and biology to model dynamic systems, including reaction kinetics, population dynamics, and biological processes. In this work, we integrate GPU-accelerated ODE…

Machine Learning · Computer Science 2024-12-02 Rakshit Kr. Singh , Aaron Rock Menezes , Rida Irfan , Bharath Ramsundar

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

Some continuous optimization methods can be connected to ordinary differential equations (ODEs) by taking continuous limits, and their convergence rates can be explained by the ODEs. However, since such ODEs can achieve any convergence rate…

Numerical Analysis · Mathematics 2022-07-15 Kansei Ushiyama , Shun Sato , Takayasu Matsuo

We describe a set of Gaussian Process based approaches that can be used to solve non-linear Ordinary Differential Equations. We suggest an explicit probabilistic solver and two implicit methods, one analogous to Picard iteration and the…

Methodology · Statistics 2014-08-19 David Barber

In this paper, we consider the initial value problem for some nonlinear second-order ODEs of Duffing type. We study the large time behavior of the solutions to this problem, from both the perspectives of mathematical and numerical analysis.…

Classical Analysis and ODEs · Mathematics 2025-04-03 Yusuke Kunimoto , Ikki Fukuda

In this article we introduce a finite difference approximation for integro-differential operators of L\'evy type. We approximate solutions of integro-differential equations, where the second order operator is allowed to degenerate. In the…

Numerical Analysis · Mathematics 2016-08-02 Konstantinos Dareiotis

The single exponential (SE) and double exponential (DE) formulas are widely recognized as efficient quadrature formulas for evaluating integrals with endpoint singularity. For integrals exhibiting algebraic singularity, explicit error…

Numerical Analysis · Mathematics 2025-07-30 Tomoaki Okayama , Kosei Arakawa , Ryo Kamigaki , Eita Yabumoto

Estimation of actual errors from the residue in iterative solutions is necessary for efficient solution of large problems when their condition number is much larger than one. Such estimators for conjugate gradient algorithms used to solve…

Numerical Analysis · Mathematics 2014-06-27 Aashish Vishwakarma , Murugesan Venkatapathi