60 citations · 68 across the 20 of their papers we have counts for
4 papers · 2 filters
Adaptive Split-MMD Training for Small-Sample Cross-Dataset P300 EEG Classification
Weiyu Chen, Arnaud Delorme
Detecting single-trial P300 from EEG is difficult when only a few labeled trials are available. When attempting to boost a small target set with a large source dataset through tran…
Data Normalization Strategies for EEG Deep Learning
Dung Truong, Arnaud Delorme
Normalization is a critical yet often overlooked component in the preprocessing pipeline for EEG deep learning applications. The rise of large-scale pretraining paradigms such as s…
Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA
Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3
Independent Component Analysis (ICA) is an important step in EEG processing for a wide-ranging set of applications. However, ICA requires well-designed studies and data collection…
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Bruno Aristimunha, Dung Truong, Pierre Guetschel +16
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-ba…