Hi,

I'm looking to train on multiple datasets which are temporal but all start at time 0 and proceed for some amount of time. I can't stack these time series together because each is a different event to conflate them would ruin the predictive capability of any model afaik. I want to train across several thousand samples of variable time length. I'm not sure how to do this with flow forecast or if you could point me in the right direction that would be helpful.

This is analogous to training on a subset of stock data. I have 10 stocks for 1 day time series each should have discrete training as they have underlying variables which differ. Any advice would be helpful happy to share the csvs I am working with. Thanks!