Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling
Abstract: Highlights•A new framework is proposed for multi-rate time series modeling under label scarcity.•Our approach can explicitly characterize multi-scale temporal dynamics.•The temporal alignment mechanism can aggregate and refine the multi-rate feature representations.•Our proposed approach achieved state-of-the-art performance on five real-world datasets.
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