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Intrinsic Associative Memory on Riemannian Manifolds: Curvature, Capacity, and Emergent Modes
Geometry does more than constrain an associative memory: curvature determines what it remembers and which states it creates. We develop intrinsic dense associative memories on Riemannian manifolds by casting memory as Epanechnikov kernel-density mode seeking. We compare geodesic and volume-corrected
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