CASE-NET combines a causal temporal encoder with adaptive channel recalibration and reports new state-of-the-art accuracy on four of six evaluated multivariate time series tasks.
Causal-oriented representation learning for time- series forecasting based on the spatiotemporal information transformation.Communications Physics, 8(1):242
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CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification
CASE-NET combines a causal temporal encoder with adaptive channel recalibration and reports new state-of-the-art accuracy on four of six evaluated multivariate time series tasks.