Neural CDEs as Correctors for Learned Time Series Models
arXiv:2512.12116v3 Announce Type: replace
Abstract: Learned time-series models, whether continuous or discrete, are widely used for forecasting the states of dynamical systems but suffer from error accumulation in multi-step forecasts. To address this…