Reviews: DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters

In this paper, authors study the graph convolution networks. Especially, the authors propose a new filter to approximate the true Fourier transformation, in the same spirit of Chebyshev filters and others. The proposed filter is based on the ARMA filter of Eq. (6). This equation is computationally heavy, so the proposed feedback-looped filter approximates the equation as in Eq.(7). Then the actual implementation of Graph Neural Network is formulated as in Eq.(12).