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Updated: May 24, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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随机时间序列的概率近似使用贝叶斯反复神经网络.

Yuhang Wang, Kaiquan Cai, Deyuan Meng

    IEEE transactions on neural networks and learning systems
    |March 3, 2025
    PubMed
    概括

    这项研究分析了贝叶斯反复神经网络的时间序列预测. 我们表明,将序列转换为潜在变量模型,并使用Bayes by Backprop对更多样本进行预测,可以提高预测的准确性和收性.

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