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Exact first and second derivatives by automatic differentiation
Author(s) -
Naumann Uwe
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200700844
Subject(s) - automatic differentiation , jacobian matrix and determinant , hessian matrix , numerical differentiation , yield (engineering) , computer science , mathematics , algorithm , mathematical analysis , computation , materials science , metallurgy
Automatic differentiation (AD) is a method for computing derivatives of outputs of numerical programs with respect to its inputs both accurately (with machine precision) and efficiently. The two basic modes of AD – forward and reverse – and combinations thereof yield products of a vector with the Jacobian, its transposed, or the Hessian, respectively. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)