20140623
Derivatives of mathematical functions are needed in various areas of computational engineering. Examples include the solution of nonlinear systems of equations and inverse problems. When the function is given in the form of a computer program, automatic differentiation (AD) enters the picture. In this set of powerful techniques, derivatives are evaluated accurately rather than approximately by divided differences. A common misconception is that AD is not capable of exploiting sparsity of Jacobian or Hessian matrices. However, there is a rich set of AD techniques based on modeling derivative computations by means of coloring various types of graphs. This talk will give an introduction to these techniques and will also present some recent results.
Category: CE SeminarTechnische Universität Darmstadt
Graduate School CE
Dolivostraße 15
D64293 Darmstadt

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