Graph Neural Networks, Deep Learning, Machine Learning, Artificial Intelligence, Gnn.
eigendecomposition of the graph Laplacian: L = UΛUT where the columns of U are the eigenvectors, and Λ is the diagonal matrix of eigenvalues λ1 ≤ … ≤ λN. The eigenvectors {ul} of L form an orthonormal Fourier basis for signals on G. The corresponding eigenvalues {λl} represent graph frequencies.