English(EN) On shallow feedforward neural networks with inputs from a topological space

新型神经网络架构可处理拓扑空间输入

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了一种新型前馈神经网络，旨在处理来自拓扑空间的输入。这种新颖的方法，称为拓扑前馈神经网络（TFNNs），已被证明能够逼近拓扑空间内的任何连续函数。作为直接应用，该研究提出了对紧致度量空间上的Kolmogorov叠加定理的逼近。 AI

影响引入了一种新颖的神经网络理论框架，有可能将其应用扩展到复杂的非欧几里得数据结构。

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arXiv cs.LG TIER_1 English(EN) · Vugar Ismailov · 2026-10-28 04:00

关于拓扑空间输入的浅层前馈神经网络

arXiv:2504.02321v3 Announce Type: replace Abstract: We study feedforward neural networks with inputs from a topological space (TFNNs). We prove a universal approximation theorem for shallow TFNNs, which demonstrates their capacity to approximate any continuous function defined on…