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原標題：KAN: Kolmogorov–Arnold Networks論文全譯
關鍵字：函數,報告,變量,符號,表示
文章來源：人工智能學家
內容字數：50170字

內容摘要：

來源：CreateAMind
KAN: Kolmogorov–Arnold Networkshttps://arxiv.org/pdf/2404.197566 討論
Application aspects:We have presented some preliminary evidences that KANs are more effective than MLPs inscience-related tasks,e.g., fitting physical equations and PDE solving.
Weexpect that KANs may also be promising for solvingNavier-Stokes equations, density functional theory, or any other tasks that can be formulated as regression or PDE solving.
We would also like to apply KANs to machine-learning-related ta

原文鏈接：KAN: Kolmogorov–Arnold Networks論文全譯

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文章來源：人工智能學家
作者微信：AItists
作者簡介：致力成為權威的人工智能科技媒體和前沿科技研究機構