DE-NOISING TASK-SPECIFIC ELECTROENCEPHALOGRAM SIGNALS USING NEURAL NETWORKS

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an auto-encoder to de-noise task specific electroencephalogram (EEG) signals. One of the methods includes training a variational auto-encoder (VAE) including to learn a plurality of parameter values of the VAE by applying, as first training input to the VAE, training data, the training data comprising electroencephalogram (EEG) data representing brain activities of individual persons when performing different tasks; and after the training, adapting the VAE for a specific task by applying, as second training input to the VAE, adaptation data, the adaptation data comprising task-specific EEG data representing brain activities of individual persons when performing the specific task.