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Updated: May 23, 2025

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在QCML数据集中,从33.5M DFT和14.7B半经验计算中获得的量子化学参考数据

Stefan Ganscha1, Oliver T Unke2, Daniel Ahlin3

  • 1Google DeepMind, Zürich, Switzerland. ganscha@google.com.

Scientific data
|March 8, 2025
PubMed
概括

新的QCML数据集提供了广泛的量子化学数据,用于训练机器学习模型,从而实现更快的属性预测. 该资源通过为开发准确的预测模型提供一个大基础来加速计算化学.

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