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Showing 1–2 of 2 results
Advanced filters: Author: Arash Vahdat Clear advanced filters

  • Great advances in protein structure prediction have been made with recent deep learning-based methods, but proteins interact with their environment and can change shape drastically when binding to ligand molecules. To predict the 3D structure of these combined protein–ligand complexes, Qiao et al. developed a generative diffusion model with biophysical constraints and geometric deep learning.

    • Zhuoran Qiao
    • Weili Nie
    • Animashree Anandkumar
    Research
    Nature Machine Intelligence
    Volume: 6, P: 195-208

  • A physics inspired two-step approach for generative machine learning model that performs stochastic downscaling, trained on three years of weather model data for Taiwan, is able to efficiently reproduce the physics of weather phenomena such as the collocation of rain with surface temperature and winds.

    • Morteza Mardani
    • Noah Brenowitz
    • Mike Pritchard
    ResearchOpen Access
    Communications Earth & Environment
    Volume: 6, P: 1-10