Puhua Niu1, Byung-Jun Yoon1,2, Xiaoning Qian1,3,2

  • 1Department of Electrical & Computer Engineering, Texas A&M University, College Station, 77843, Texas, United States.

PubMed
概括

本研究介绍了有效的贝叶斯优化方法,用于校准流行病学模型. 这些新的灰盒方法提高了计算昂贵的模型的校准速度和准确性.

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