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cs.LG2026
Anchoring the Eigengap: Cross-Modal Spectral Stabilization for Sample-Efficient Representation Learning
Nikhil J. Dhinagar, Vidhi Chhatbar, Chirag Jagad +6
Deep vision models degrade sharply in low-data regimes, particularly in medical imaging where labeled samples are scarce. We show this arises not merely from overfitting but from a…
cs.LG2026
How Much Data is Enough? The Zeta Law of Discoverability in Biomedical Data, featuring the enigmatic Riemann zeta function
Paul M. Thompson
How much data is enough to make a scientific discovery? As biomedical datasets scale to millions of samples and AI models grow in capacity, progress increasingly depends on predict…
cs.AI2026
Multi-modal Imputation for Alzheimer's Disease Classification
Abhijith Shaji, Tamoghna Chattopadhyay, Sophia I. Thomopoulos +3
Deep learning has been successful in predicting neurodegenerative disorders, such as Alzheimer's disease, from magnetic resonance imaging (MRI). Combining multiple imaging modaliti…