Kyoung-Min Kim

Neural scaling laws and evolution of learnable activation functions of Kolmogorov-Arnold networks

Kolmogorov-Arnold Networks (KANs) represent a compelling alternative to traditional Multi-Layer Perceptron (MLP)-based neural networks. By employing activation functions as learnable elements, KANs offer superior interpretability, making them suited for scientific domains. In this work, we investigate the neural scalin...