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English(EN) Variational Kolmogorov-Arnold Network

Kolmogorov-Arnold网络通过自动基学习和实践指南进行演进

研究人员推出InfinityKAN,一个新颖的框架,可自动选择Kolmogorov-Arnold网络(KANs)中的基函数,KANs是传统多层感知机的理论基础替代品。这种新方法将基函数数量建模为潜在变量,使其可以在训练期间学习,无需手动调整超参数。在各种数据集上的实验表明,InfinityKAN在没有手动指定的情况下,实现了与现有KANs相当或更优的性能。 AI

影响 自动调整KANs的超参数,可能简化其采用并提高在各种任务上的性能。

排序理由 该集群包含两篇arXiv论文,详细介绍了Kolmogorov-Arnold网络(KANs)的进展和指南。

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Kolmogorov-Arnold网络通过自动基学习和实践指南进行演进

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该集群包含两篇arXiv论文,详细介绍了Kolmogorov-Arnold网络(KANs)的进展和指南。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Francesco Alesiani, Henrik Christiansen, Federico Errica ·

    变分Kolmogorov-Arnold网络

    arXiv:2507.02466v2 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) offer a theoretically grounded alternative to multi-layer perceptrons by representing multivariate functions as compositions of univariate basis functions. However, a critical limitation of KANs…

  2. arXiv cs.LG TIER_1 English(EN) · Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales ·

    Kolmogorov-Arnold网络的实践者指南

    arXiv:2510.25781v5 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive over…