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STONED-SELFIES

This repository contains code for the paper: Beyond Generative Models: Superfast Traversal, Optimization, Novelty, Exploration and Discovery (STONED) Algorithm for Molecules using SELFIES. By: AkshatKumar Nigam, Robert Pollice, Mario Krenn, Gabriel dos Passos Gomes, Alán Aspuru-Guzik

Prerequisites:

For cloning the repository, please have a look at the Branch Navigator section.

Before running the code, please ensure you have the following:

Experiment Navigator:

  • Please have a look at our Tutorial Document. There we provide quick details on how to form local chemical subspaces, generating chemical paths & obtaining median molecules.
  • Experiment B: Formation of Local Chemical Spaces
  • Experiment C: Chemical Paths and Rediscovery (with a GA)
  • Experiment D: Interpolation via Chemical Path formation
  • Experiment E: Median Molecules for Photovoltaics (obtaining median molecules)

Questions, problems?

Make a github issue 😄. Please be as clear and descriptive as possible. Please feel free to reach out in person: (akshat[DOT]nigam[AT]mail[DOT]utoronto[DOT]ca, rob[DOT]pollice[AT]utoronto[DOT]ca, mario[DOT]krenn[AT]utoronto[DOT]ca , gabriel[DOT]gomes[AT]utoronto[DOT]ca)

License

Apache License 2.0

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This repository contains code for the paper: Beyond Generative Models: Superfast Traversal, Optimization, Novelty, Exploration and Discovery (STONED) Algorithm for Molecules using SELFIES

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  • Jupyter Notebook 88.1%
  • Python 11.9%