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20242026
most citedSegment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations

2 citations · 2 across the 5 of their papers we have counts for

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cs.HC2025

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…

cs.HC2025

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…