Learning Invariant Representations From EEG via Adversarial Inference
Discovering and exploiting shared, invariant neural activity in electroencephalogram (EEG) based classification tasks is of significant interest for generalizability of decoding models across subjects or EEG recording sessions. While deep neural networks are recently emerging as generic EEG feature...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8981912/ |