Semantically-correlated memories in a dense associative model

• URL: http://arxiv.org/abs/2404.07123v3
• Date: Sun, 2 Jun 2024 08:29:45 GMT
• Title: Semantically-correlated memories in a dense associative model
• Authors: Thomas F Burns,
• Abstract summary: I introduce a novel associative memory model named Correlated Associative Memory (CDAM) CDAM integrates both auto- and hetero-association in a unified framework for continuous-valued memory patterns. It is theoretically and numerically analysed, revealing four distinct dynamical modes.
• Score: 2.7195102129095003
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: I introduce a novel associative memory model named Correlated Dense Associative Memory (CDAM), which integrates both auto- and hetero-association in a unified framework for continuous-valued memory patterns. Employing an arbitrary graph structure to semantically link memory patterns, CDAM is theoretically and numerically analysed, revealing four distinct dynamical modes: auto-association, narrow hetero-association, wide hetero-association, and neutral quiescence. Drawing inspiration from inhibitory modulation studies, I employ anti-Hebbian learning rules to control the range of hetero-association, extract multi-scale representations of community structures in graphs, and stabilise the recall of temporal sequences. Experimental demonstrations showcase CDAM's efficacy in handling real-world data, replicating a classical neuroscience experiment, performing image retrieval, and simulating arbitrary finite automata.

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