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Kolmogorov-Arnold Networks (KANs), recently proposed by researchers at MIT, present a promising alternative to traditional Multi-Layer Perceptrons (MLPs), demonstrating superior performance in terms of both accuracy and interpretability. The goal of this project is to further advance the architecture of KANs by enhancing their computational graph through various research directions. These include optimizing loss functions, refining activation functions, developing more effective initialization schemes, and improving learning processes. https://arxiv.org/abs/2404.19756 https://arxiv.org/abs/2407.13044 https://arxiv.org/abs/2407.20667
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