ms-Mamba: Multi-scale Mamba for Time-Series Forecasting

• URL: http://arxiv.org/abs/2504.07654v1
• Date: Thu, 10 Apr 2025 11:06:57 GMT
• Title: ms-Mamba: Multi-scale Mamba for Time-Series Forecasting
• Authors: Yusuf Meric Karadag, Sinan Kalkan, Ipek Gursel Dino,
• Abstract summary: ms-Mamba incorporates multiple temporal scales by using multiple Mamba blocks with different sampling rates.<n>Our experiments on many benchmarks demonstrate that ms-Mamba outperforms state-of-the-art approaches.
• Score: 9.008102132057733
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The problem of Time-series Forecasting is generally addressed by recurrent, Transformer-based and the recently proposed Mamba-based architectures. However, existing architectures generally process their input at a single temporal scale, which may be sub-optimal for many tasks where information changes over multiple time scales. In this paper, we introduce a novel architecture called Multi-scale Mamba (ms-Mamba) to address this gap. ms-Mamba incorporates multiple temporal scales by using multiple Mamba blocks with different sampling rates ($\Delta$s). Our experiments on many benchmarks demonstrate that ms-Mamba outperforms state-of-the-art approaches, including the recently proposed Transformer-based and Mamba-based models.

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