Adversarial invariant feature learning is applied to one-hour EEG speller data to remove drowsiness effects from event-related features using recording block order as the nuisance variable.
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Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects
Adversarial invariant feature learning is applied to one-hour EEG speller data to remove drowsiness effects from event-related features using recording block order as the nuisance variable.