Developmental Trajectory

Developmental trajectory research investigates how systems, whether biological (e.g., infant brains) or artificial (e.g., neural networks), change and learn over time. Current studies focus on modeling these trajectories using techniques like diffusion models for image completion and optimal transport methods for inferring dynamic processes, often comparing the learning paths of artificial systems to those observed in human development (e.g., language acquisition, physical understanding). Understanding these trajectories is crucial for improving artificial intelligence, informing educational practices, and gaining insights into the mechanisms underlying human cognitive development and its vulnerabilities.