2 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Graph-Based Learning of Spectro-Topographical EEG Representations with Gradient Alignment for Brain-Computer Interfaces
Prithila Angkan, Amin Jalali, Paul Hungler +1
We present a novel graph-based learning of EEG representations with gradient alignment (GEEGA) that leverages multi-domain information to learn EEG representations for brain-comput…
Multi-Domain EEG Representation Learning with Orthogonal Mapping and Attention-based Fusion for Cognitive Load Classification
Prithila Angkan, Amin Jalali, Paul Hungler +1
We propose a new representation learning solution for the classification of cognitive load based on Electroencephalogram (EEG). Our method integrates both time and frequency domain…
Learning Time-Series Representations by Hierarchical Uniformity-Tolerance Latent Balancing
Amin Jalali, Milad Soltany, Michael Greenspan +1
We propose TimeHUT, a novel method for learning time-series representations by hierarchical uniformity-tolerance balancing of contrastive representations. Our method uses two disti…