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Showing 1–2 of 2 results
Advanced filters: Author: Daniel Flam-Shepherd Clear advanced filters

  • Generative models for the novo molecular design attract enormous interest for exploring the chemical space. Here the authors investigate the application of chemical language models to challenging modeling tasks demonstrating their capability of learning complex molecular distributions.

    • Daniel Flam-Shepherd
    • Kevin Zhu
    • Alán Aspuru-Guzik
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-10

  • A variational autoencoder is trained on a dataset of quantum optics experiment configurations and learns an interpretable representation of the relationship between experiment setup and quantum entanglement. The approach can be used to explore new experiment designs with specific, highly entangled states.

    • Daniel Flam-Shepherd
    • Tony C. Wu
    • Alán Aspuru-Guzik
    Research
    Nature Machine Intelligence
    Volume: 4, P: 544-554