SL-S4Wave combines contrastive learning with a multiscale S4 encoder to outperform baselines in arrhythmia detection and EEG tasks while showing strong label efficiency and robustness on long sequences.
Therefore, in the ablation experiments, we set different values ofdto investigate the effect of kernel size on model performance
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SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models
SL-S4Wave combines contrastive learning with a multiscale S4 encoder to outperform baselines in arrhythmia detection and EEG tasks while showing strong label efficiency and robustness on long sequences.