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Browse All Reviews > Mathematics Of Computing (G) > Numerical Analysis (G.1) > Quadrature And Numerical Differentiation (G.1.4) > Automatic Differentiation (G.1.4...)
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1-4 of 4
Reviews about "Automatic Differentiation (G.1.4...)":
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Evaluating derivatives: principles and techniques of algorithmic differentiation
Griewank A., Walther A., Society for Industrial and Applied Mathematics, Philadelphia, PA, 2008. 460 pp. Type: Book (9780898716597)
Evaluating derivatives of functions is a problem frequently encountered in various areas of scientific computing. This is especially important if the task at hand comes from a nonlinear problem, regardless of whether the precise backgr...
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Dec 12 2008 |
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Accurate numerical derivatives in MATLAB
Shampine L. ACM Transactions on Mathematical Software 33(4): 26-es, 2007. Type: Article
The use of finite difference methods for approximating derivatives has historic roots (recall the definition of the derivative from calculus). The need for derivatives is fundamental in calculations solving nonlinear problems, as the u...
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Feb 25 2008 |
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Using AD to solve BVPs in MATLAB
Shampine L., Ketzscher R., Forth S. ACM Transactions on Mathematical Software 31(1): 79-94, 2005. Type: Article
A method for the numerical solution of two-point boundary value problems for ordinary differential equations, using MATLAB, is discussed in this paper. A classical algorithm for this problem has been proposed by Kierzenka and Shampine ...
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Apr 20 2005 |
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Algorithm 799: revolve: an implementation of checkpointing for the reverse or adjoint mode of computational differentiation
Griewank A., Walther A. ACM Transactions on Mathematical Software 26(1): 19-45, 2000. Type: Article
This is an excellent paper, describing a variant (“revolve”) of the basic form for reverse differentiation for computing the gradient of a scalar valued function, which enables computing this gradient of a function ...
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Oct 1 2000 |
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