Dynamic graph representation serves as a framework for modelling systems whose structure evolves over time, incorporating changes in nodes and edges to capture temporal patterns. Link prediction ...

A new model called GA-ODE combines graph attention networks with ordinary differential equation constraints to predict ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...

Called Dynamic Clustering for Channel Pruning (DCCP), the method reduced the floating-point operations of ResNet-50 by 68.52% ...