Graph Filter

Graph filters are mathematical tools used to process data residing on graphs, aiming to extract meaningful information by considering the underlying graph structure. Current research focuses on improving graph filter performance in scenarios with heterophilic graphs (where connected nodes have dissimilar properties), developing online graph filtering methods for dynamic graphs, and designing efficient algorithms like polynomial filters to reduce computational costs. These advancements are significant for various applications, including recommendation systems, node classification, and clustering, where efficient and accurate processing of complex graph data is crucial.