在Flight数据集上,MSGNet优于TimesNet(当前SOTA),平均减少了 (从0.265降至0.208)和 (从0.372降至0.321)的MSE和MAE。尽管TimesNet使用了多尺度信息,但它采用了一种纯粹的计算机视觉模型来捕捉序列间和序列内相关性,这对时间序列数据并不是很有效。Autoformer在Flight数据集上表现出色,这可能归功于其建立的互相关机...
This repo provides PyTorch Implementation ofMSG-Net (ours)andNeural Style (Gatys et al. CVPR 2016), which has been included byModelDepot. We also provideTorch implementationandMXNet implementation. Tabe of content [arXiv] [project] Hang Zhang,Kristin Dana @article{zhang2017multistyle, title={Mul...
MSGNet使用多头自注意力机制来捕捉单个时间序列内的时序模式,并通过softmax函数根据振幅值对不同尺度的表示进行加权聚合。 定义了多头自注意力: 定义了尺度聚合: 5. 输出层 (Output Layer) 最后,MSGNet使用线性投影将聚合后的多尺度特征映射到预测的时间序列上。 04 实验结果 文中的实验结果部分详细评估了模型在多...
convolution layer to autonomously learn diverse inter-series correlations within each time scale. Extensive experiments are conducted on several real-world datasets to showcase the effectiveness of MSGNet. Furthermore, MSGNet possesses the ability to automatically learn explainable multi-scale inter-...
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting (AAAI2024) - YoZhibo/MSGNet
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convolution layer to autonomously learn diverse inter-series correlations within each time scale. Extensive experiments are conducted on several real-world datasets to showcase the effectiveness of MSGNet. Furthermore, MSGNet possesses the ability to automatically learn explainable multi-scale inter-...
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting (AAAI2024) - 777-q/MSGNet
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