2 papers
cs.LG2026
Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets
Laurits Dixen, Stefan Heinrich, Paolo Burelli
Classification of EEG signals using shallow Convolutional Neural Networks (CNNs) is a prevalent and successful approach across a variety of fields. Most of these models use indepen…
cs.LG2025
Exploring Deep Learning Models for EEG Neural Decoding
Laurits Dixen, Stefan Heinrich, Paolo Burelli
Neural decoding is an important method in cognitive neuroscience that aims to decode brain representations from recorded neural activity using a multivariate machine learning model…