My understanding is that paramenters of neurals are shared in Multivariate prediction and they can learn some correlations between series. There is less training time in Multivariate prediction. I wonder if that's right. Could you please explain any basic principles of Multivariate prediction with LSTM or recommend related papers to me? Thank you.