2023年2月1日 · MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting Huiqiang Wang , Jian Peng , Feihu Huang , Jince Wang , Junhui Chen , Yifei Xiao …

termed as Multi-scale Isometric Convolution Network (MICN), is more efficient with linear complexity with respect to the sequence length. Our experiments on five benchmark datasets …

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as Multi-scale Isometric Convolution Network (MICN), is more efficient with linear complexity about the sequence length with suitable convolution kernels. Our experiments on six …

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2024年9月25日 · To address these limitations, we propose a novel framework called Med-MICN (Medical Multi-dimensional Interpretable Concept Network). Med-MICN provides …

PatchTST (Nie et al., 2022); (3) Models use Convolutional Neural Networks (CNNs), like MICN and TimesNet (Wang et al., 2022; Wu et al., 2022). It’s worth noting that these categories are …

(2022) and MICN Wang et al. (2023) proposed multi-scale hybrid decomposition approach based on Moving Average to extract various seasonal and trend-cyclical parts of time series. …

regression. MICN (Wang et al., 2023) also decomposes input series into seasonal and trend terms, and then integrates the global and local context for forecasting. As for the multi …

Interest-based item representation generated by MICN shared with original model takes user diverse interest information in whole model. The contributions of this paper can be …