Author

Shinichi Nakajima

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#machine learning Preprint Oct 2026

Decoupling Time and Space: A Temporally Conditioned Refinement for EEG Source Imaging

Electroencephalography (EEG) offers millisecond temporal resolution, but inferring underlying neural sources is a severely ill-posed spatial inverse problem. While deep learning has advanced spatial reconstruction, current architectures face a critical dilemma: frame-by-frame models discard vital temporal context, wher...

Marco Morik, Jesse Palarus, C. Vidaurre 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