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arXiv · 2503.01702

Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks

Nandi Schoots·Mattia Jacopo Villani·Niels uit de Bos
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Abstract

Kolmogorov-Arnold Networks are a new family of neural network architectures which holds promise for overcoming the curse of dimensionality and has interpretability benefits (arXiv:2404.19756). In this paper, we explore the connection between Kolmogorov Arnold Networks (KANs) with piecewise linear (univariate real) functions and ReLU networks. We provide completely explicit constructions to convert a piecewise linear KAN into a ReLU network and vice versa.

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Nandi Schoots, Mattia Jacopo Villani, Niels uit de Bos. 2025-03-03. Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks. https://arxiv.org/abs/2503.01702

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