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#machine learning Preprint Oct 2026

SPDAlign: Interpretable Riemannian Alignment for EEG Forward Modeling Shifts

Electroencephalography (EEG) based brain-computer interfaces enable direct brain-to-device communication for applications such as rehabilitation and communication. However, their practical utility is often limited as the non-stationary nature of the EEG data introduces distribution shifts across domains (e.g., sessions...

Shang-Lin Li, Shi-Wen Chu, Okan Koç et al. · 0 citations
#machine learning Preprint Sep 2026

Explaining Hyperbolic Neural Networks via Geometry-Aware Relevance Propagation

Hyperbolic neural networks introduce geometric operations that require explicit treatment in relevance propagation. Equivalent geometric realizations can produce different feature attributions, even when local relevance is conserved. We study this problem through Geometric Representation Invariance (GRI), a specializat...

Pin Xiong, Shang-Lin Li, Yi Ding et al. · 0 citations

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