[R] KAN: Kolmogorov-Arnold Networks

**Paper**: [https://arxiv.org/abs/2404.19756](https://arxiv.org/abs/2404.19756)

**Code**: [https://github.com/KindXiaoming/pykan](https://github.com/KindXiaoming/pykan)

**Quick intro**: [https://kindxiaoming.github.io/pykan/intro.html](https://kindxiaoming.github.io/pykan/intro.html)

**Documentation**: [https://kindxiaoming.github.io/pykan/](https://kindxiaoming.github.io/pykan/)

**Abstract**:

>Inspired by the Kolmogorov-Arnold representation theorem, we propose **Kolmogorov-Arnold Networks** (**KANs**) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have *fixed* activation functions on *nodes* ("neurons"), KANs have *learnable* activation functions on *edges* ("weights"). KANs have no linear weights at all -- every weight parameter is replaced by a univariate function parametrized as a spline. We show that this seemingly simple change makes KANs outperform MLPs in terms of …

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