Trajectory Model

Trajectory modeling focuses on characterizing and predicting the movement of objects or agents over time, aiming to understand underlying patterns and behaviors. Current research emphasizes robust model architectures, such as transformers and variational autoencoders, to handle noisy data, complex interactions, and uncertainty, often incorporating causal learning to mitigate confounding factors. These advancements have significant implications across diverse fields, including anomaly detection, personalized medicine, robotics, and autonomous systems, enabling improved prediction, control, and decision-making.