Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting

ArXi:2605.23402v1 Announce Type: cross Effectively modeling non-stationary dynamics in probabilistic multivariate time series(MTS) forecasting requires balancing expressiveness with robustness. Existing parametric approaches benefit from strong inductive biases but lack flexibility, whereas deep generative models struggle to capture complex temporal dependencies without extensive data and computation. We