Abstract. This report describes MSAD, a tool that applies source transformation automatic differentiation to MATLAB programs involving arbitrary vector-valued functions. The transformed programs compute both the results of the original program and the first derivatives. The current version of MSAD performs a complete source transformation for the forward mode of AD by specialising and inlining operations from the fmad and derivvec classes of the MAD package. This implementation benefits by eliminating overheads due to operator overloading in MAD while preserving the optimised derivative combination operations from thederivvec class. MSAD also inherits from MAD the use of MATLAB’s sparse data-type to propagate directional derivatives. To aid...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machin...
Often the most robust and efficient algorithms for the solution of large-scale problems involving no...
We present MSAD, a source transformation implementation of forward mode automatic differentiation fo...
The interactive programming environment MATLAB is increasingly gaining popularity by enabling the us...
Mad is a Matlab library of functions and utilities for the automatic differentiation of Matlab func-...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
The ADiMat software is a tool that offers automatic differentiation of Matlab functions using a hyb...
The ADiMat software is a tool that offers Automatic Differentiation of any Matlab function using a ...
MAD is a Matlab library of functions and utilities for the automatic differentiation of Matlab func...
The ADiMat software is a tool that offers automatic differentiation of any Matlab function using a h...
An object-oriented method is presented that generates derivatives of functions defined by MATLAB com...
Automatic differentiation—the mechanical transformation of numeric computer programs to calculate de...
An object-oriented method is presented that computes without truncation error derivatives of functio...
Automatic differentiation --- the mechanical transformation of numeric computer programs to calculat...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machin...
Often the most robust and efficient algorithms for the solution of large-scale problems involving no...
We present MSAD, a source transformation implementation of forward mode automatic differentiation fo...
The interactive programming environment MATLAB is increasingly gaining popularity by enabling the us...
Mad is a Matlab library of functions and utilities for the automatic differentiation of Matlab func-...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
The ADiMat software is a tool that offers automatic differentiation of Matlab functions using a hyb...
The ADiMat software is a tool that offers Automatic Differentiation of any Matlab function using a ...
MAD is a Matlab library of functions and utilities for the automatic differentiation of Matlab func...
The ADiMat software is a tool that offers automatic differentiation of any Matlab function using a h...
An object-oriented method is presented that generates derivatives of functions defined by MATLAB com...
Automatic differentiation—the mechanical transformation of numeric computer programs to calculate de...
An object-oriented method is presented that computes without truncation error derivatives of functio...
Automatic differentiation --- the mechanical transformation of numeric computer programs to calculat...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machin...
Often the most robust and efficient algorithms for the solution of large-scale problems involving no...