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- Automatic_differentiation abstract "In mathematics and computer algebra, automatic differentiation (AD), also called algorithmic differentiation or computational differentiation, is a set of techniques to numerically evaluate the derivative of a function specified by a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations (addition, subtraction, multiplication, division, etc.) and elementary functions (exp, log, sin, cos, etc.). By applying the chain rule repeatedly to these operations, derivatives of arbitrary order can be computed automatically, accurately to working precision, and using at most a small constant factor more arithmetic operations than the original program.Automatic differentiation is not: Symbolic differentiation, or Numerical differentiation (the method of finite differences).These classical methods run into problems: symbolic differentiation leads to inefficient code (unless carefully done) and faces the difficulty of converting a computer program into a single expression, while numerical differentiation can introduce round-off errors in the discretization process and cancellation. Both classical methods have problems with calculating higher derivatives, where the complexity and errors increase. Finally, both classical methods are slow at computing the partial derivatives of a function with respect to many inputs, as is needed for gradient-based optimization algorithms. Automatic differentiation solves all of these problems.".
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- Automatic_differentiation wikiPageID "734787".
- Automatic_differentiation wikiPageRevisionID "605667448".
- Automatic_differentiation hasPhotoCollection Automatic_differentiation.
- Automatic_differentiation subject Category:Computer_algebra.
- Automatic_differentiation subject Category:Differential_calculus.
- Automatic_differentiation type Genre.
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- Automatic_differentiation type TopicalConcept.
- Automatic_differentiation type Concept.
- Automatic_differentiation comment "In mathematics and computer algebra, automatic differentiation (AD), also called algorithmic differentiation or computational differentiation, is a set of techniques to numerically evaluate the derivative of a function specified by a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations (addition, subtraction, multiplication, division, etc.) and elementary functions (exp, log, sin, cos, etc.).".
- Automatic_differentiation label "Automatic differentiation".
- Automatic_differentiation label "Automatisches Differenzieren".
- Automatic_differentiation label "Diferenciación automática".
- Automatic_differentiation label "Diferenciação automática".
- Automatic_differentiation label "自動微分".
- Automatic_differentiation label "自動微分".
- Automatic_differentiation sameAs Automatisches_Differenzieren.
- Automatic_differentiation sameAs Diferenciación_automática.
- Automatic_differentiation sameAs 自動微分.
- Automatic_differentiation sameAs Diferenciação_automática.
- Automatic_differentiation sameAs m.036tpg.
- Automatic_differentiation sameAs Q787371.
- Automatic_differentiation sameAs Q787371.
- Automatic_differentiation wasDerivedFrom Automatic_differentiation?oldid=605667448.
- Automatic_differentiation depiction AutomaticDifferentiationNutshell.png.
- Automatic_differentiation isPrimaryTopicOf Automatic_differentiation.
