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English(EN) Phases in a class of associative memories via hidden neurons

新研究通过隐藏神经元探索联想记忆的相 · 跟踪到2个来源

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员分析了一类称为H类的联想记忆，该类联想记忆利用了具有隐藏神经元的二分结构。这种结构允许在多项式和指数负载机制下研究检索动力学和存储容量。分析揭示了不同的相，包括顺磁相、凝聚相和冻结相，并强调了隐藏神经元如何充当检索的序参量。该研究还区分了多项式负载和指数负载之间的串扰统计数据，表明可见和隐藏拉格朗日量分别在固定稳定性和存储规模方面起着双重作用。 AI

影响 这项研究为联想记忆模型的行为提供了理论见解，可能为未来神经网络架构的进步提供信息。

排序理由 该集群包含两篇相同的arXiv预印本，详细介绍了关于联想记忆的理论研究。

在 arXiv cs.NE (Neural & Evolutionary) 阅读 →

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新研究通过隐藏神经元探索联想记忆的相 · 跟踪到2个来源

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该集群包含两篇相同的arXiv预印本，详细介绍了关于联想记忆的理论研究。
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报道来源 [3]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Masato Taki ·

    通过隐藏神经元实现一类联想记忆中的阶段

    Associative memory in the Hopfield network is attractor dynamics in a disordered many-body system, and higher-order and exponential extensions turn its retrieval update into softmax attention. The polynomial and exponential regimes have been analyzed by different methods, with no…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    通过隐藏神经元实现一类联想记忆中的阶段

    Associative memory in the Hopfield network is attractor dynamics in a disordered many-body system, and higher-order and exponential extensions turn its retrieval update into softmax attention. The polynomial and exponential regimes have been analyzed by different methods, with no…

  3. arXiv stat.ML TIER_1 English(EN) · Toshihiro Ota, Masato Taki ·

    通过隐藏神经元实现一类联想记忆中的阶段

    arXiv:2609.10976v1 Announce Type: cross Abstract: Associative memory in the Hopfield network is attractor dynamics in a disordered many-body system, and higher-order and exponential extensions turn its retrieval update into softmax attention. The polynomial and exponential regime…

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