Automatic differentiation of third order derivatives is implemented in C++. The implementation uses uses object-orientation and operator overloading to perform the differentiation. A short introduction to operator overloading is done with complex numbers. Automatic differentiation of univariate functions is then extended to the second and third derivatives of multivariate function. A set of functions for benchmarking is given, and numerical results which describe the cost of calculating the derivatives are presented.Master i Informatikk - optimeringMAMN-INFOPINFO
Developing code for computing the first- and higher-order derivatives of a function by hand can be v...
This article describes approaches to computing second-order derivatives with automatic differentiati...
An object-oriented method is presented that computes without truncation error derivatives of functio...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
summary:Automatic differentiation is an effective method for evaluating derivatives of function, whi...
The C++ package ADOL-C described in this paper facilitates the evaluation of first and higher deriva...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
In this paper, we introduce automatic differentiation as a method for computing derivatives of large...
We study the high order reverse mode of Automatic Differentiation (AD) in the dissertation. Automati...
Full text of this paper is not available in the UHRAThis paper gives an introduction to a number of ...
AbstractAlgorithmic differentiation (AD) is a mathematical concept which evolved over the last decad...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
Developing code for computing the first- and higher-order derivatives of a function by hand can be v...
This article describes approaches to computing second-order derivatives with automatic differentiati...
An object-oriented method is presented that computes without truncation error derivatives of functio...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
summary:Automatic differentiation is an effective method for evaluating derivatives of function, whi...
The C++ package ADOL-C described in this paper facilitates the evaluation of first and higher deriva...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
In this paper, we introduce automatic differentiation as a method for computing derivatives of large...
We study the high order reverse mode of Automatic Differentiation (AD) in the dissertation. Automati...
Full text of this paper is not available in the UHRAThis paper gives an introduction to a number of ...
AbstractAlgorithmic differentiation (AD) is a mathematical concept which evolved over the last decad...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
Developing code for computing the first- and higher-order derivatives of a function by hand can be v...
This article describes approaches to computing second-order derivatives with automatic differentiati...
An object-oriented method is presented that computes without truncation error derivatives of functio...