Edge Function

Edge functions, representing data associated with connections rather than nodes in a network, are a burgeoning research area aiming to model complex relationships within various systems. Current research focuses on developing sophisticated models, such as Gaussian processes and tensor decompositions, to analyze and predict these functional edge data, often incorporating techniques like Hodge decomposition for improved interpretability and handling irregular data through tensor completion. These advancements have implications across diverse fields, improving the accuracy and efficiency of tasks ranging from network analysis and flow prediction to semi-supervised learning and 3D object recognition.