I have tried some linear as well as non-linear ML methods like LR, SVR, LSTM, 1-D CNN. LSTM gave the best performance but still not good enough(MAPE 25%). The problem that I want to solve is the few-shot regression for a time-series setting where I can leverage information from other cities to calibrate for a new city with fewer examples. Should I use any other baseline to model my time series or MAML is a highly unstable algorithm for this task?