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This project uses a Variational Autoencoder (VAE) to generate SMILES strings for novel compound generation. The VAE model is trained on a dataset of existing chemical compounds and can generate new, valid SMILES strings, which may represent potentially new and useful chemical entities.
RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactions" (https://advances.sciencemag.org/content/7/15/eabe4166).