205 citations · 464 across the 19 of their papers we have counts for
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cs.LG2021
Holistic Semi-Supervised Approaches for EEG Representation Learning
Guangyi Zhang, Ali Etemad
Recently, supervised methods, which often require substantial amounts of class labels, have achieved promising results for EEG representation learning. However, labeling EEG data i…
cs.LG2021★ 2 cited
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition
Guangyi Zhang, Ali Etemad
EEG-based emotion recognition often requires sufficient labeled training samples to build an effective computational model. Labeling EEG data, on the other hand, is often expensive…
cs.LG2021★ 7 cited
Distilling EEG Representations via Capsules for Affective Computing
Guangyi Zhang, Ali Etemad
Affective computing with Electroencephalogram (EEG) is a challenging task that requires cumbersome models to effectively learn the information contained in large-scale EEG signals,…