Weighted Network

Weighted networks represent complex systems by assigning weights to connections between nodes, reflecting the strength or type of interaction. Current research focuses on developing models and algorithms that handle diverse weight types (scalar, matrix, signed), incorporating expert knowledge (e.g., in medical image analysis), and addressing challenges like network transferability and efficient pruning in large-scale applications. These advancements improve the accuracy and interpretability of network analysis across various fields, from social sciences and medical imaging to materials science and deep learning, enabling better understanding and prediction of complex system dynamics.