Dependency Modeling

Dependency modeling focuses on identifying and representing relationships between elements within complex systems, aiming to improve prediction accuracy and understanding of system behavior. Current research emphasizes diverse applications, from analyzing discourse structures using dependency parsing and graph neural networks to forecasting multivariate time series by modeling inter-series dependencies across various frequency components. These advancements are improving performance in areas like natural language processing, time series analysis, and engineering design, offering more robust and efficient solutions for complex problems.