Dynamical mean-field analysis shows slow dynamics near retrieval boundaries in high-order Hopfield models persist even without diagonal interactions, pointing to intrinsic high-order effects.
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Dense associative memory retrieval converges geometrically with O(log N) time and tolerates adversarial corruptions under separation and bounded-interference conditions, achieving capacity scaling Θ(N^{n-1}).
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Testing the Role of Diagonal Interactions in High-Order Hopfield Models via Dynamical Mean-Field Theory
Dynamical mean-field analysis shows slow dynamics near retrieval boundaries in high-order Hopfield models persist even without diagonal interactions, pointing to intrinsic high-order effects.
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Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness
Dense associative memory retrieval converges geometrically with O(log N) time and tolerates adversarial corruptions under separation and bounded-interference conditions, achieving capacity scaling Θ(N^{n-1}).