Graph Convolutional Networks (GCN) and their variants utilize learnable weight matrices and nonlinear activation functions to extract features from data. The selection of activation functions and ...

In recent days, the information about electrical activity is obtained in the form of Electro-Cardo-Diograms (ECG) which is become a typical way of monitoring heart rhythm and function of patients. In ...

Activation energy characterization of competing reactions is a costly but crucial step for understanding the kinetic relevance of distinct reaction pathways, product yields, and myriad other ...

The input layer encompasses the entire population graph, while a SoftMax activation function follows the output layer. To evaluate the performance of our model, we employed a five-fold ...

They usually contain rich structure information, and how to effectively extract inherent features of them is of great significance on the determination of function or traits in medicine and biology.