Epileptic seizures arise from complex, nonlinear interactions within brain networks, yet reliable electroencephalographic (EEG) prediction remains challenging due to the nonstationary and heterogeneous nature of neural dynamics. Existing methods typically analyze EEG data as static or weakly time-dependent snapshots. C...
Zi-Han Wang, Dai-Xin Li, Gui-Lin Wang et al.· Machine Learning: Science an...· 0 citations
Despite the availability of various sequence analysis models, comparative genomic analysis remains a challenge in genomics, genetics, and phylogenetics. Commutative algebra, a fundamental tool in algebraic geometry and number theory, has rarely been used in data and biological sciences. In this study, we introduce comm...
F. Suwayyid, Yuta Hozumi, Mushal Zia et al.· Nature Communications· 13 citations· ⚡2
The computational results indicate that the proposed Persistent Sheaf Laplacian learning (PSLL) model achieves strong predictive performance across benchmark datasets, highlighting its potential as an interpretable and mathematically grounded framework with promising generalizability for molecular machine learning and...
Mushal Zia, Benjamin Jones, Guo-Wei Wei· 0 citations
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