In many settings, data is collected as multiple time series, where each recorded time series is an observation of some underlying dynamical process of interest. These observations are often time-marked with known event times, and one desires to do a range of standard analyses. When there is only one time marker, one simply aligns the observations temporally on that marker. When multiple time-markers are present and are at dierent times on dierent time series observations, these analyses are more dicult. We describe a Gaussian Process model for analyzing multiple time series with multiple time markings, and we test it on a variety of data.
['John P. Cunningham', 'Zoubin Ghahramani', 'Carl Edward Rasmussen']
Gaussian Processes for time-marked time-series data