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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation (2nd Revised edition)

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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation - Griewank, Andreas, and Walther, Andrea
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Algorithmic, or automatic, differentiation (AD) is a growing area of theoretical research and software development concerned with the accurate and efficient evaluation of derivatives for function evaluations given as computer programs. The resulting derivative values are useful for all scientific computations that are based on linear, quadratic, or higher order approximations to nonlinear scalar or vector functions. AD has been applied in particular to optimization, parameter identification, nonlinear equation solving, the ...

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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation 2008, Society for Industrial and Applied Mathematics (SIAM), Philadelphia

ISBN-13: 9780898716597

2nd Revised edition

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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation 1987, Society for Industrial and Applied Mathematics (SIAM), Philadelphia

ISBN-13: 9780898714517

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