Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

Abstract Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their superior performance in various graph analytical tasks. Mini-batch ...

Repository of the netin package to generate random scale-free graph generators proposed by members of the Network Inequality CSH group ...

Therefore, understanding the impact of microbes on disease is essential. The DuGEL model leverages the strengths of graph convolutional neural network (GCN) and graph attention network (GAT), ensuring ...

Abstract A network consists of two interdependent parts: the network topology or graph, consisting of the links between nodes and the network dynamics, specified by some governing equations. A crucial ...

Recently, network diversity based security metrics is attracting researcher's interests. Several efforts have been devoted into the network diversity modeling, for the purpose of evaluating network ...

We propose a 5G bearer network fault prediction method based on graph random walk. By analyzing the association relationship of network devices’ alarm information, we construct an alarm association ...