DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis

Understand

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.
• Recently, Mamba has emerged as a promising linear-time alternative with high expressiveness.