Dense Associative Memory for Pattern Recognition (Krotov & Hopfield, 2016)

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• Large Associative Memory Problem in Neurobiology and Machine Learning (Krotov & Hopfield, 2020)concept0.839
  Paper proposing neurally plausible instantiation of Hopfield/transformer with feature neurons and memory neurons; used to derive place cell interpretation.
• On a Model of Associative Memory with Huge Storage Capacity (Demircigil et al., 2017)concept0.817
  Analytical result showing exponential power activation allows memory storage scaling as 2^(N/2); cited in context of Hopfield scaling.
• Associative Memoryconcept0.780
  Memory system that stores patterns in connection weights and recalls them from partial or noisy cues; property of Hopfield networks and evolved networks
• Efficient hardware support for large n-dimensional associative memory would enable implementations of diverse object models.finding0.778
• Associative memory modelframework0.778
• Hopfield network can store multiple patterns, recall them via content-addressable memory, and generalise to novel patterns with the same underlying structure.finding0.764
  Summary of known Hopfield network capabilities used as a model for collective computation.
• Associative learning criterion can occur in gene regulatory networks and non-neural morphogenetic agentshypothesis0.763
• The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation (Whittington et al., 2020)concept0.758
  Prior paper by the same lead author introducing TEM; the neuroscience model whose relationship to transformers is the central topic.