Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities
Researchers have introduced the Sinc Kolmogorov-Arnold Network (SincKAN), a novel neural network architecture that utilizes Sinc interpolation for learnable activation functions. This approach aims to improve the representation of both smooth functions and those with singularities, making it particularly effective for solving partial differential equations (PDEs) with physics-informed neural networks. Experimental results indicate that SincKANs outperform traditional methods in various applications. AI