[D] Classification of irregular time series
I have been working on classification of variable stars using light curves. However, the curves have different number of data points, from 40 data points up to 100. I have been training my network by randomly removing points until having about 50 points per star, and also augmented the data with different combination of eliminated points, but it seems to introduce a lot of loss.
I am interested in different approaches or ideas on how to handle the irregularity.