Bayesian complete-pooling models slightly improve calibration and prediction uncertainty for cross-subject motor-imagery EEG, but the effects are practically negligible.
Transfer learning promotes acquisition of individual bci skills.PNAS Nexus, 3(2): pgae076, 02 2024
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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram
Bayesian complete-pooling models slightly improve calibration and prediction uncertainty for cross-subject motor-imagery EEG, but the effects are practically negligible.