Automatic differentiation: Difference between revisions
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==Definition== | ==Definition== | ||
'''Automatic differentiation''' ('''AD''') also called '''algorithmic differentiation''' or '''computational differentiation''' is a set of techniques used to calculate a derivative, or derivatives, at a point or set of points. The goal is for the final answer to be numeric, but it differs from [[ | '''Automatic differentiation''' ('''AD''') also called '''algorithmic differentiation''' or '''computational differentiation''' is a set of techniques used to calculate a derivative, or derivatives, at a point or set of points. The goal is for the final answer to be numeric, but it differs from [[numerical differentiation]] in that the method partly uses [[symbolic differentiation]] to simplify expressions before evaluating them numerically. | ||
Latest revision as of 21:02, 9 May 2014
Definition
Automatic differentiation (AD) also called algorithmic differentiation or computational differentiation is a set of techniques used to calculate a derivative, or derivatives, at a point or set of points. The goal is for the final answer to be numeric, but it differs from numerical differentiation in that the method partly uses symbolic differentiation to simplify expressions before evaluating them numerically.