This paper is concerned with the efficient computation of sparse Jacobian matrices of nonlinear vector maps using automatic differentiation (AD). Specifically, we propose the use of a graph coloring technique, bi-coloring, to exploit the sparsity of the Jacobian matrix J and thereby allow for the efficient determination of J using AD software. We analyze both a direct scheme and a substitution process. We discuss the results of numerical experiments indicating significant practical potential of this approach
The background of this thesis is algorithmic differentiation (AD) of in practice very computationall...
AbstractWe describe a graph coloring problem associated with the determination of mathematical deriv...
In many nonlinear problems it is necessary to estimate the Jacobian matrix of a nonlinear mapping $...
This paper is concerned with the efficient computation of sparse Jacobian matrices of nonlinear vect...
The computation of large sparse Jacobian matrices is required in many important large-scale scientif...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Summary. Using a model from a chromatographic separation process in chemical engineer-ing, we demons...
Simulations and optimizations are carried out to investigate real-world problems in science and engi...
The computation of a sparse Hessian matrix H using automatic differentiation (AD) can be made effici...
The computation of sparse Jacobians is a common subproblem in iterative numerical algorithms. The sp...
We revisit the role of graph coloring in modeling problems that arise in efficient estimation of la...
AbstractWe review the extended Jacobian approach to automatic differentiation of a user-supplied fun...
Given a mapping with a sparse Jacobian matrix, the problem of minimizing the number of function eval...
viii, 83 leaves ; 29 cm.There has been extensive research activities in the last couple of years to ...
. Automatic differentiation (AD) is a technique that augments computer codes with statements for the...
The background of this thesis is algorithmic differentiation (AD) of in practice very computationall...
AbstractWe describe a graph coloring problem associated with the determination of mathematical deriv...
In many nonlinear problems it is necessary to estimate the Jacobian matrix of a nonlinear mapping $...
This paper is concerned with the efficient computation of sparse Jacobian matrices of nonlinear vect...
The computation of large sparse Jacobian matrices is required in many important large-scale scientif...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Summary. Using a model from a chromatographic separation process in chemical engineer-ing, we demons...
Simulations and optimizations are carried out to investigate real-world problems in science and engi...
The computation of a sparse Hessian matrix H using automatic differentiation (AD) can be made effici...
The computation of sparse Jacobians is a common subproblem in iterative numerical algorithms. The sp...
We revisit the role of graph coloring in modeling problems that arise in efficient estimation of la...
AbstractWe review the extended Jacobian approach to automatic differentiation of a user-supplied fun...
Given a mapping with a sparse Jacobian matrix, the problem of minimizing the number of function eval...
viii, 83 leaves ; 29 cm.There has been extensive research activities in the last couple of years to ...
. Automatic differentiation (AD) is a technique that augments computer codes with statements for the...
The background of this thesis is algorithmic differentiation (AD) of in practice very computationall...
AbstractWe describe a graph coloring problem associated with the determination of mathematical deriv...
In many nonlinear problems it is necessary to estimate the Jacobian matrix of a nonlinear mapping $...