most citedEEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification

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eess.SP2024

Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models

Mingzhi Chen, Yiyu Gui, Yuqi Su +3

Electroencephalogram (EEG) classification has been widely used in various medical and engineering applications, where it is important for understanding brain function, diagnosing d…

eess.SP2024★ 1 cited

EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification

Yiyu Gui, MingZhi Chen, Yuqi Su +2

In recent years, with the development of deep learning, electroencephalogram (EEG) classification networks have achieved certain progress. Transformer-based models can perform well…