Deep learning for molecular generation and optimization - a review of the state of the art

@article{Elton2019DeepLF,
  title={Deep learning for molecular generation and optimization - a review of the state of the art},
  author={D. Elton and Zois Boukouvalas and M. Fuge and P. W. Chung},
  journal={ArXiv},
  year={2019},
  volume={abs/1903.04388}
}
In the space of only a few years, deep generative modeling has revolutionized how we think of artificial creativity, yielding autonomous systems which produce original images, music, and text. Inspired by these successes, researchers are now applying deep generative modeling techniques to the generation and optimization of molecules—in our review we found 45 papers on the subject published in the past two years. These works point to a future where such systems will be used to generate lead… Expand
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