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Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

License: MIT License

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cheminformatics pytorch materials-science materials-informatics python deep-learning variational-autoencoder molecular-structures machine-learning drug-discovery

molecular-vae's Introduction

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

MIT license made-with-python

Pytorch implementation of the paper Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules by:

  • Rafa Gómez-Bombarelli
  • David Duvenaud
  • José Miguel Hernández-Lobato
  • Jorge Aguilera-Iparraguirre
  • Timothy Hirzel
  • Ryan P. Adams
  • Alán Aspuru-Guzik

References

Portions of the code have been re-used from the following repositories:

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