MVPFormer, a transformer with disentangled content, time, and channel attention, achieves expert-level zero-shot seizure detection on 50 unseen patients and near-SOTA results on speech decoding, alongside the largest open iEEG dataset.
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A foundation model with multi-variate parallel attention to generate neuronal activity
MVPFormer, a transformer with disentangled content, time, and channel attention, achieves expert-level zero-shot seizure detection on 50 unseen patients and near-SOTA results on speech decoding, alongside the largest open iEEG dataset.