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School of Artificial Intelligence and Computer Science
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Riemannian self-attention can revolutionize EEG decoding by overcoming the limitations of traditional metrics, leading to more accurate brain-computer interfaces.
A new framework for EEG decoding boosts generalization across datasets while maintaining low training overhead and no extra inference costs.
