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English(EN) MambaSL: Exploring Single-Layer Mamba for Time Series Classification

MedMamba和MambaSL使用状态空间模型推进时间序列分类

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了MedMamba，一种基于Mamba状态空间模型的新型架构，专门用于对ECG和EEG等医疗时间序列数据进行分类。该方法通过有效捕捉长距离依赖关系和跨通道关系，克服了传统模型的局限性，并在多个基准数据集上超越了当前最先进的方法。此外，另一项独立研究MambaSL探索了单层Mamba在时间序列分类中的有效性，在30个数据集上建立了可复现的基准，并展示了Mamba作为该任务的强大骨干的潜力。 AI

影响 为时间序列分类引入了新的基于Mamba的架构和基准，有望改善医疗诊断和数据分析。

排序理由 两篇研究论文介绍了基于Mamba模型用于时间序列分类任务的新架构和基准。

在 arXiv cs.LG 阅读 →

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MedMamba和MambaSL使用状态空间模型推进时间序列分类

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两篇研究论文介绍了基于Mamba模型用于时间序列分类任务的新架构和基准。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · ZhengXiao He, Huayu Li, Xiwen Chen, Janet M Roveda, Jinghao Wen, Siyuan Tian, Ao Li ·

    MedMamba：为医疗时间序列分类重塑Mamba

    arXiv:2605.05214v1 Announce Type: cross Abstract: Medical time series, such as electrocardiograms (ECG) and electroencephalograms (EEG), exhibit complex temporal dynamics and structured cross-channel dependencies, posing fundamental challenges for automated analysis. Conventional…

  2. arXiv cs.LG TIER_1 English(EN) · Yoo-Min Jung, Leekyung Kim ·

    MambaSL：探索用于时间序列分类的单层Mamba

    arXiv:2604.15174v2 Announce Type: replace Abstract: Despite recent advances in state space models (SSMs) such as Mamba across various sequence domains, research on their standalone capacity for time series classification (TSC) has remained limited. We propose MambaSL, a framework…

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