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Published March 10, 2023 | Version v2
Software Open

Automated patent extraction powers generative modeling in focused chemical spaces: Code release

Creators

  • 1. Massachusetts Institute of Technology
  • 2. Swiss Airtainer SA
  • 3. National Tsing Hua University

Description

Code accompanying paper on "Automated patent extraction powers generative modeling in focused chemical spaces". The training data and model checkpoints can be found in a separate repository at 10.5281/zenodo.7996464. If you use this data/code, please cite the following manuscript:

@article{patents-generative2023,
  title={Automated patent extraction powers generative modeling in focused chemical spaces},
  author={Subramanian, Akshay and Greenman, Kevin P. and Gervaix, Alexis and Yang, Tzuhsiung and G{\'{o}}mez-Bombarelli, Rafael},
  journal={TBD},
  doi={TBD},
  year={2023}
}

Files

Patent_paper_final_code.zip

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