dailyai.report

JointFM introduces a foundation model that learns to predict joint probability distributions of coupled time series by training on an infinite stream of synthetic SDE equations. This approach eliminates the need for brittle SDE calibration and reduces computational cost, offering a versatile tool for global forecasting in finance, climate, and epidemiology.