Advances in Automatic Differentiation [electronic resource]/ edited by Christian H. Bischof, H. Martin Bücker, Paul Hovland, Uwe Naumann, Jean Utke.

By:

Bischof, Christian H

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Series: Lecture Notes in Computational Science and Engineering ; 64Publication details: Berlin, Heidelberg: Springer Berlin Heidelberg, 2008.Description: digitalISBN:

9783540689423

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Additional physical formats: Printed edition:: No titleDDC classification:

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In: Springer eBooksSummary: This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization .

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This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization .

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