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

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

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

python machine-learning natural-language-processing deep-learning chemistry cheminformatics molecular-structures jupyter-notebook pytorch drug-discovery materials-science materials-informatics variational-autoencoder

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