This adjacency matrix represents which nodes in your graph are connected by edges and which are not. You can then use this matrix to compute a sequence of numbers, called eigenvalues, that provide ...

but it is still competitive compared to other algorithms. We can get the following conclusions: 1. The multi-order adjacency matrix propagation of LGNN enables it to iteratively transmit information ...

Recent studies show that GCN-based classification methods can facilitate the accuracy increase of learning algorithms ... in the topology graph and increase the flexibility of the framework, we learn ...

ABSTRACT: The optical response of subwavelength silver nanowires arranged periodically on silica has been analyzed numerically by the differential method improved by the S matrix algorithm. Our ...

However, this direct use of existing algorithms causes a duplicated enumeration ... In this paper, we also prove that if self-loops are allowed in a graph, then the number of closed patterns in the ...