AI RESEARCH
DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis
arXiv CS.LG
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ArXi:2601.05527v2 Announce Type: replace Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within this realm, Transformers have emerged as the predominant architecture due to their strong ability to capture pairwise dependencies. However, Transformer-based models suffer from quadratic computational complexity and high memory overhead, limiting their scalability and practical deployment in long-term and large-scale MTS modeling.