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English(EN) How Long Is the Coast of a Neuron? Resolution-Dependent Interaction Order and Computational Capacity

新论文使用曼德尔布罗特集来分析神经计算分辨率

一篇新的arXiv论文探讨了观察神经计算的分辨率如何影响其表观结构和计算能力。该研究引入了一种尺度索引分解方法,将预测信息与直接依赖关系区分开来,并与残余信息区分开来。它表明,投影可以将高阶依赖关系转化为成对结构,可能在不一定增加总预测信息的情况下增加由直接依赖关系捕获的信息比例。该框架表明,使用点神经元或直接群体方法的模型在特定尺度上建立描述,但未能完全识别产生观察到的关系的更精细的计算过程。 AI

影响 为理解观测尺度如何影响对神经网络计算的解释提供了理论框架。

排序理由 该条目是发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新论文使用曼德尔布罗特集来分析神经计算分辨率

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该条目是发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Nima Dehghani ·

    神经元的海岸线有多长?分辨率依赖的相互作用顺序与计算能力

    Mandlebrot's coastline paradox reframes measurement as a joint property of an object and its ruler. Here we ask how observational resolution shapes the apparent structure of neural computation. We introduce a scale-indexed decomposition that separates the predictive information c…