English(EN) The minimal width of universal $p$-adic ReLU neural networks

研究人员探索 $p$-adic ReLU 神经网络的最小宽度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

一篇新发表在 arXiv 上的研究论文探讨了 $p$-adic 神经网络的理论基础。该研究确定了这些网络在紧开子集内实现连续函数通用逼近特性所需的最小宽度。研究特别关注 ReLU 激活函数的 $p$-adic 类似物，并考虑了包括 $L_q$ 和 $C_1$ 范数在内的各种范数。 AI

影响这项理论工作有助于理解神经网络架构及其在非标准数学框架中的逼近能力。

排序理由发布在 arXiv 上的学术论文，详细介绍了神经网络的理论特性。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · S\'andor Z. Kiss, Ambrus P\'al · 2026-11-05 05:00

通用 $p$-adic ReLU 神经网络的最小宽度

arXiv:2603.00064v2 Announce Type: replace-cross Abstract: We determine the minimal width of $p$-adic neural networks with the universal approximation property for continuous $\mathbb Q_p$-valued functions on compact open subsets with respect to the $L_q$ norms and the $C_1$ norm,…