Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders

Measuring similarities between unlabeled time series trajectories is an important problem in many domains such as medicine, economics, and vision. It is often unclear what is the appropriate metric to use because of the complex nature of noise in the trajectories (e.g.