[jethkl]

It's great to see research in this field, I know there is opportunity here, and I hope to someday benefit from progress. But I skimmed the paper, and it doesn't appear solve a problem that I have. From the practical standpoint, what I want from a time series tool includes: 1) a small set of simple levers that I can review and tune 2) short training time for any input sets of size O(10k) to O(100k) (this covers seconds/day, minutes/week, hours/year) 3) the process of train + forecast can run fine on CPUs -- not GPUs with low memory overhead 4) decent out of the box performance that basically passes the sniff test and 5) a simple way to include regressors. I've enough experience to have learned to be wary of fully automated tuning, benchmark performance metrics, elaborate models, etc.