Pietro Tesi

Machines that Predict Trajectories from Templates

Claudio De Persis, Pietro Tesi

We study trajectory prediction from libraries of stored output templates. Given the past of an unknown trajectory, the goal is to predict its future without identifying the state-space model that generated it. We show that libraries of trajectories generated by one or more dynami…Read more