[eigen] Eigen-AD: Algorithmic Differentiation of the Eigen Library

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Dear all,

We would like to draw your attention to a new fork of Eigen with support for Algorithmic Differentiation (AD) in the context of AD by overloading in C++. Important new features include highly efficient first and higher derivatives of Eigen solvers as well as compatibility with a wide range of AD software tools. See


for details including benchmark results. Please contact info@xxxxxxxxxxxxxxxxxxx for access to the software.

We look forward to further discussions with potential users and other AD software tool developers.

With kind regards

Patrick Peltzer, Johannes Lotz, Uwe Naumann
Informatik 12 (STCE), RWTH Aachen University, Germany

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