Abstract
On top of theoretical Algorithmic Differentiation as described in most of this book, there is also the computer science art of Automatic Algorithmic Differentiation. This is the art of writing code that performs the Algorithmic Differentiation automatically. The developments required are relatively heavy at the start, but from there on, there should be only a minimal development cost.
Big brother is watching you: AD tapes – Automatic AD saves programing time, not execution time – Human are still useful to computers – On n’oublie rien de rien. On s’habitue c’est tout
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References
Naumann, U. (2012). The Art of Differentiating Computer Programs. An Introduction to Algorithmic Differentiation. Philadelphis:SIAM.
Naumann, U. and du Toit, J. (2014). Adjoint algorithmic differentiation tool support for typical numerical patterns in computational finance. Technical report, RWTH Aachen University.
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Henrard, M. (2017). Automatic Algorithmic Differentiation. In: Algorithmic Differentiation in Finance Explained . Financial Engineering Explained. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-53979-9_4
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DOI: https://doi.org/10.1007/978-3-319-53979-9_4
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Publisher Name: Palgrave Macmillan, Cham
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Online ISBN: 978-3-319-53979-9
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