arXiv:2405.06721
공식 코드 · Papers with Code
Kolmogorov-Arnold Networks are Radial Basis Function Networks
원문 초록
This short paper is a fast proof-of-concept that the 3-order B-splines used in Kolmogorov-Arnold Networks (KANs) can be well approximated by Gaussian radial basis functions. Doing so leads to FastKAN, a much faster implementation of KAN which is also a radial basis function (RBF) network.
함께 살펴볼 논문
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Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models
Automated Modeling Method for Pathloss Model Discovery
"KAN you hear me?" Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding
TK-Mamba: Marrying KAN with Mamba for Text-Driven 3D Medical Image Segmentation
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes
토론
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