Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error
2017 · Journal of Chemical Theory and Computation · 672 citations
https://doi.org/10.1021/acs.jctc.7b00577
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Samuel S. Schoenholz
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Samuel S. Schoenholz is an academic researcher from OpenAI (United States). The author has contributed to research in topics: Neural Networks and Applications & Material Dynamics and Properties & Machine Learning in Materials Science. The author has an h-index of 35, co-authored 83 publications.
ORCID: 0000-0003-1909-9226Papers by this author
worksA structural approach to relaxation in glassy liquids
2016 · Nature Physics · 449 citations
https://doi.org/10.1038/nphys3644
Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods
2015 · Physical Review Letters · 435 citations
https://doi.org/10.1103/physrevlett.114.108001
Unveiling the predictive power of static structure in glassy systems
2020 · Nature Physics · 327 citations
https://doi.org/10.1038/s41567-020-0842-8
Heterogeneous Activation, Local Structure, and Softness in Supercooled Colloidal Liquids
2019 · Physical Review Letters · 61 citations
https://doi.org/10.1103/physrevlett.122.028001
End-to-end differentiability and tensor processing unit computing to accelerate materials’ inverse design
2023 · npj Computational Materials · 9 citations
https://doi.org/10.1038/s41524-023-01080-x
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