Do you trust derivatives or differences?
type: Item
instance of: scholarly article
title: Do you trust derivatives or differences?
zbMATH Open document ID: 1352.65668
author: Jorge J. Moré
author: Stefan M. Wild
published in: Journal of Computational Physics
publication date: 2016-12-20T00:00:00Z
Mathematics Subject Classification ID: 65Y04
zbMATH DE Number: 6666371
zbMATH Keywords: computational noise
zbMATH Keywords: numerical differentiation
zbMATH Keywords: automatic differentiation
zbMATH Keywords: iterative solvers
describes a project that uses: ADiMat
describes a project that uses: INTLAB
describes a project that uses: MINRES-QLP
describes a project that uses: SparseMatrix
describes a project that uses: MINRES
MaRDI profile type: Publication
full work available at URL: j.jcp.2014.04.056
OpenAlex ID: W2043458938
cites work: Estimating Computational Noise
cites work: Q4949347
cites work: Evaluating Derivatives
cites work: On the numerical stability of algorithmic differentiation
cites work: Parallel iterative methods for sparse linear systems
cites work: Iterative Krylov Methods for Large Linear Systems
cites work: Estimating Derivatives of Noisy Simulations
cites work: The university of Florida sparse matrix collection
cites work: MINRES-QLP: A Krylov Subspace Method for Indefinite or Singular Symmetric Systems
cites work: Relative Distance--An Error Measure in Round-Off Error Analysis
cites work: Jacobian-free Newton-Krylov methods: a survey of approaches and applications.
cites work: A Jacobian-free Newton-Krylov algorithm for compressible turbulent fluid flows
DOI: 10.1016/J.JCP.2014.04.056
description: scientific article; zbMATH DE number 6666371