Analysis of the generalization ability of graph neural networks in cross-subject EEG emotion recognition

A calibration-free, entropy-guided graph neural network (EGGN) to enhance accuracy, Architectural interpretability, and fairness in EEG-based emotion recognition, which enables robust, interpretable, and fair emotion decoding from electroencephalography across subjects and datasets.