CVKAN: Complex-Valued Kolmogorov-Arnold Networks

• URL: http://arxiv.org/abs/2502.02417v3
• Date: Tue, 22 Apr 2025 15:09:46 GMT
• Title: CVKAN: Complex-Valued Kolmogorov-Arnold Networks
• Authors: Matthias Wolff, Florian Eilers, Xiaoyi Jiang,
• Abstract summary: We show how to transfer a complex-valued Kolmogorov-Arnold Network into the complex domain.<n>Our proposed CVKAN is more stable and performs on par or better than real-valued KANs.
• Score: 6.095572174539791
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this work we propose CVKAN, a complex-valued Kolmogorov-Arnold Network (KAN), to join the intrinsic interpretability of KANs and the advantages of Complex-Valued Neural Networks (CVNNs). We show how to transfer a KAN and the necessary associated mechanisms into the complex domain. To confirm that CVKAN meets expectations we conduct experiments on symbolic complex-valued function fitting and physically meaningful formulae as well as on a more realistic dataset from knot theory. Our proposed CVKAN is more stable and performs on par or better than real-valued KANs while requiring less parameters and a shallower network architecture, making it more explainable.

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