Tools for algorithmic differentiation (AD) provide accurate derivatives ...
Algorithmic differentiation (AD) is a set of techniques that provide par...
Objective. Algorithmic differentiation (AD) can be a useful technique to...
On the one hand Sobolev gradient smoothing can considerably improve the
...
We present the new software OpDiLib, a universal add-on for classical
op...
With more efficient structures, last trends in aeronautics have witnesse...
For operator overloading Algorithmic Differentiation tools, the
identifi...
We propose a universal method for the evaluation of generalized standard...
Most machine learning methods require careful selection of hyper-paramet...
Current training methods for deep neural networks boil down to very high...
Algorithmic Differentiation (AD) can be used to automate the generation ...
There are several AD tools available, which all implement different
stra...