Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery

@article{Preuer2018FrchetCD,
  title={Fr{\'e}chet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery},
  author={Kristina Preuer and Philipp Renz and Thomas Unterthiner and Sepp Hochreiter and G{\"u}nter Klambauer},
  journal={Journal of chemical information and modeling},
  year={2018},
  volume={58 9},
  pages={
          1736-1741
        }
}
The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, method comparison is difficult because of various flaws of the currently employed evaluation metrics. We propose an evaluation metric for generative models called Fréchet ChemNet distance (FCD). The advantage of the FCD over previous metrics is that it can detect whether generated molecules are diverse and have similar chemical and biological… 
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