A new algorithm opens the door for using artificial intelligence and machine learning to study the interactions that happen ...

Adjacency matrices are a way to represent the connections between the vertices on a graph numerically. Adjacency matrices are square matrices where the corresponding rows and columns represent each of ...

The boost of signal processing on graph has recently solicited research on the problem of identifying (learning) the graph underlying the observed signal values according to given criteria, such as ...

A. Roy, A. Thakur and U. Satija, "VGAResNet: A Unified Visibility Graph Adjacency Matrix-Based Residual Network for Chronic Obstructive Pulmonary Disease Detection Using Lung Sounds," in IEEE Sensors ...

To maximize the homogeneity of these two distinct graphs, we design an improved semi-supervised contrastive loss. In order to enrich scarce label information, we propose a self-supervised mechanism to ...

In the case of an undirected graph, the adjacency_matrix. class does not use a full V x V matrix but instead uses a lower triangle (the diagonal and below) since the matrix for an undirected graph is ...

Link graphs are a part of ranking and for that reason it’s important to understand what they are how your strategies make sense with this way of mapping the Internet.