2017
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
NeurIPS 2017poster
We introduce a hierarchical model which allows to estimate a group-average piecewise-geodesic trajectory in the Riemannian space of measurements and individual variability. This model falls into the well defined mixed-effect models. The subject-specific trajectories are defined through spatial and t…