2026
MANIFOLDFORMER: GEOMETRIC DEEP LEARNING FOR NEURAL DYNAMICS ON RIEMANNIAN MANIFOLDS
ICASSP 2026poster
Existing EEG foundation models mainly treat neural signals as generic time series in Euclidean space, ignoring the intrinsic geometric structure of neural dynamics that constrains brain activity to low-dimensional manifolds. This fundamental mismatch between model assumptions and neural geometry lim…