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Flow-based spectral kernel attention (FSKA), a framework for learning expressive nonstationary attention kernels, is proposed and it is shown that expressive kernel learning enables a simplified attention design with removed query--key projections and fixed orthogonal value projections, resulting in a more parameter-ef...
Molecular biomarkers have transformed the biological definition of Alzheimer’s disease (AD), but they do not directly quantify the dynamic consequences of pathology on brain function. Sleep quantitative electroencephalography (qEEG) provides a complementary functional readout. We frame sleep qEEG as an artificial-intel...
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