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POPL
2007
ACM

Lazy multivariate higher-order forward-mode AD

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Lazy multivariate higher-order forward-mode AD
A method is presented for computing all higher-order partial derivatives of a multivariate function Rn R. This method works by evaluating the function under a nonstandard interpretation, lifting reals to multivariate power series. Multivariate power series, with potentially an infinite number of terms with nonzero coefficients, are represented using a lazy data structure constructed out of linear terms. A complete implementation of this method in SCHEME is presented, along with a straightforward exposition, based on Taylor expansions, of the method's correctness.
Barak A. Pearlmutter, Jeffrey Mark Siskind
Added 03 Dec 2009
Updated 03 Dec 2009
Type Conference
Year 2007
Where POPL
Authors Barak A. Pearlmutter, Jeffrey Mark Siskind
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