A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning

@article{Srajer2018ABO,
  title={A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning},
  author={F. Srajer and Z. Kukelova and A. Fitzgibbon},
  journal={Optimization Methods and Software},
  year={2018},
  volume={33},
  pages={889 - 906}
}
Algorithmic differentiation (AD) allows exact computation of derivatives given only an implementation of an objective function. Although many AD tools are available, a proper and efficient implementation of AD methods is not straightforward. The existing tools are often too different to allow for a general test suite. In this paper, we compare 15 ways of computing derivatives including 11 automatic differentiation tools implementing various methods and written in various languages (C++, F… Expand
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