Graph Wavelet

Graph wavelets are mathematical tools used to analyze and process data represented as graphs, aiming to extract meaningful features and patterns at multiple scales. Current research focuses on developing novel graph wavelet-based neural network architectures, such as multi-scale graph wavelet convolutional networks, for tasks like graph classification, traffic prediction, and analysis of complex systems like brain networks and 3D point clouds. These advancements improve the accuracy and efficiency of analyzing complex data structures, with applications ranging from early disease diagnosis to optimizing transportation systems.