FAME learns to route heterogeneous time series to a budgeted subset of forecasting experts using a multidimensional forecastability fingerprint mined from validation performance, achieving 12.4% MSE reduction on a 5,000+ machine industrial dataset while activating 1.92 experts per series on average.
AutoGluon-TimeSeries: AutoML for probabilistic time series forecasting,
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FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting
FAME learns to route heterogeneous time series to a budgeted subset of forecasting experts using a multidimensional forecastability fingerprint mined from validation performance, achieving 12.4% MSE reduction on a 5,000+ machine industrial dataset while activating 1.92 experts per series on average.