Longitudinal Dataset

Longitudinal datasets, encompassing repeated observations of individuals or systems over time, are crucial for understanding dynamic processes across diverse fields. Current research emphasizes developing robust methods for analyzing these datasets, particularly focusing on handling high-dimensionality, missing data, and complex temporal dependencies using techniques like deep learning (e.g., LSTMs, neural ODEs), optimal transport, and Bayesian modeling. This work is significant because it enables more accurate predictions, improved causal inference, and deeper insights into phenomena ranging from human behavior and health to technological systems and ecological dynamics.