A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis

arXiv:2310.11959v2 Announce Type: replace
Abstract: Time series data, including univariate and multivariate ones, are characterized by unique composition and complex multi-scale temporal variations. They often require special consideration of decomposition and multi-scale modeling to analyze. Existing deep learning methods on this best fit to univariate time series only, and have not sufficiently considered sub-series modeling and decomposition completeness. To address these challenges, we propose MSD-Mixer, a Multi-Scale Decomposition MLP-Mixer, which learns to explicitly decompose and represent the input time series …

abstract analysis analyze arxiv cs.ai cs.lg data deep learning mlp modeling multivariate scale series temporal time series type