12th European Workshop on Automatic Differentiation with Emphasis on Applications to DAEs

Automatic Differentiation (AD) is a set of techniques based on the mechanical application of the chain rule to obtain derivatives of a function given as a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations such as additions or elementary functions such as exp(). By applying the chain rule of derivative calculus repeatedly to these operations, derivatives of arbitrary order can be computed automatically, and accurate to working precision. The workshop provides a well established forum for active researchers in this area.

Principal Investigators
Griewank, Andreas Prof. Dr. (Details) (Non-linear Optimization)

Duration of Project
Start date: 11/2011
End date: 12/2011

Last updated on 2020-11-03 at 23:17