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

[Patrick Peltzer <peltzer@xxxxxxxxxxxxxxxxxxx>]

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

https://arxiv.org/abs/1911.12604

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