<ul><li>Kolmogorov-Arnold Networks (KANs) are neural networks that feature learnable activation functions on the edges of the network.</li><li>KANs do not use traditional linear weights and offer enhanced interpretability and visualization compared to MLPs.</li><li>Empirically, KANs outperform MLPs in various tasks and require fewer parameters.</li><li>KANs are suitable for scientific research and have applications in discovering new mathematical and physical laws.</li></ul>

Simple Explanation of Kolmogorov-Arnold Networks (KANs)

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